From cc50f8cad0f608cd2fb9d385f664fc4f53277b2b Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 29 Sep 2021 14:38:38 +0200 Subject: Reduce noise in nlmixr.mmkin output in examples --- R/nlmixr.R | 39 +- docs/dev/pkgdown.yml | 2 +- docs/dev/reference/Rplot001.png | Bin 43845 -> 43816 bytes docs/dev/reference/nlmixr.mmkin-1.png | Bin 127508 -> 127414 bytes docs/dev/reference/nlmixr.mmkin.html | 4190 +-------------------------------- man/nlmixr.mmkin.Rd | 39 +- 6 files changed, 99 insertions(+), 4171 deletions(-) diff --git a/R/nlmixr.R b/R/nlmixr.R index 5f7950ed..f8fffba9 100644 --- a/R/nlmixr.R +++ b/R/nlmixr.R @@ -7,7 +7,8 @@ nlmixr::nlmixr #' #' This function uses [nlmixr::nlmixr()] as a backend for fitting nonlinear mixed #' effects models created from [mmkin] row objects using the Stochastic Approximation -#' Expectation Maximisation algorithm (SAEM). +#' Expectation Maximisation algorithm (SAEM) or First Order Conditional +#' Estimation with Interaction (FOCEI). #' #' An mmkin row object is essentially a list of mkinfit objects that have been #' obtained by fitting the same model to a list of datasets using [mkinfit]. @@ -51,20 +52,31 @@ nlmixr::nlmixr #' f_mmkin_parent_tc <- mmkin(c("SFO", "FOMC", "DFOP"), ds, error_model = "tc", #' cores = 1, quiet = TRUE) #' -#' f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem") -#' f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei") +#' library(nlmixr) +#' f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem", +#' control = saemControl(print = 0)) +#' f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei", +#' control = foceiControl(print = 0)) #' -#' f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem") -#' f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei") +#' f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem", +#' control = saemControl(print = 0)) +#' f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei", +#' control = foceiControl(print = 0)) #' -#' f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem") -#' f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei") +#' f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem", +#' control = saemControl(print = 0)) +#' f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei", +#' control = foceiControl(print = 0)) #' -#' f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem") -#' f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei") +#' f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem", +#' control = saemControl(print = 0)) +#' f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei", +#' control = foceiControl(print = 0)) #' -#' f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem") -#' f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei") +#' f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem", +#' control = saemControl(print = 0)) +#' f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei", +#' control = foceiControl(print = 0)) #' #' AIC( #' f_nlmixr_sfo_saem$nm, f_nlmixr_sfo_focei$nm, @@ -76,9 +88,8 @@ nlmixr::nlmixr #' AIC(nlme(f_mmkin_parent["FOMC", ])) #' AIC(nlme(f_mmkin_parent["HS", ])) #' -#' # nlme is comparable to nlmixr with focei, saem finds a better -#' # solution, the two-component error model does not improve it -#' plot(f_nlmixr_fomc_saem) +#' # The FOCEI fit of FOMC with constant variance or the tc error model is best +#' plot(f_nlmixr_fomc_saem_tc) #' #' sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), #' A1 = mkinsub("SFO")) diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml index e52da77d..a975d20f 100644 --- a/docs/dev/pkgdown.yml +++ b/docs/dev/pkgdown.yml @@ -11,7 +11,7 @@ articles: web_only/benchmarks: benchmarks.html web_only/compiled_models: compiled_models.html web_only/dimethenamid_2018: dimethenamid_2018.html -last_built: 2021-09-27T18:09Z +last_built: 2021-09-28T09:12Z urls: reference: https://pkgdown.jrwb.de/mkin/reference article: https://pkgdown.jrwb.de/mkin/articles diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png index c26c864f..c1666cff 100644 Binary files a/docs/dev/reference/Rplot001.png and b/docs/dev/reference/Rplot001.png differ diff --git a/docs/dev/reference/nlmixr.mmkin-1.png b/docs/dev/reference/nlmixr.mmkin-1.png index 851d363d..3e8f67fd 100644 Binary files a/docs/dev/reference/nlmixr.mmkin-1.png and b/docs/dev/reference/nlmixr.mmkin-1.png differ diff --git a/docs/dev/reference/nlmixr.mmkin.html b/docs/dev/reference/nlmixr.mmkin.html index 568078c6..61f5ac07 100644 --- a/docs/dev/reference/nlmixr.mmkin.html +++ b/docs/dev/reference/nlmixr.mmkin.html @@ -42,7 +42,8 @@ +Expectation Maximisation algorithm (SAEM) or First Order Conditional +Estimation with Interaction (FOCEI)." /> @@ -148,7 +149,8 @@ Expectation Maximisation algorithm (SAEM)." />

This function uses nlmixr::nlmixr() as a backend for fitting nonlinear mixed effects models created from mmkin row objects using the Stochastic Approximation -Expectation Maximisation algorithm (SAEM).

+Expectation Maximisation algorithm (SAEM) or First Order Conditional +Estimation with Interaction (FOCEI).

# S3 method for mmkin
@@ -289,4135 +291,40 @@ obtained by fitting the same model to a list of datasets using f_mmkin_parent_tc <- mmkin(c("SFO", "FOMC", "DFOP"), ds, error_model = "tc",
   cores = 1, quiet = TRUE)
 
-f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem")
+library(nlmixr)
+
#> 
+#> Attaching package: ‘nlmixr’
#> The following object is masked from ‘package:mkin’:
+#> 
+#>     saem
f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem",
+  control = saemControl(print = 0))
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> RxODE 1.1.1 using 8 threads (see ?getRxThreads)
-#>   no cache: create with `rxCreateCache()`
#> 1:    86.5083   -3.1968    4.1673    1.7173   48.7028
-#> 2:    87.3628   -3.1468    3.9589    1.6315   45.1225
-#> 3:    86.8866   -3.2249    3.7610    1.8212   43.0034
-#> 4:    85.9210   -3.2427    3.5729    1.7302   39.4197
-#> 5:    85.8539   -3.2018    3.3943    1.7234   38.2933
-#> 6:    85.6934   -3.2262    3.2246    1.6843   39.0348
-#> 7:    85.7421   -3.2696    4.1298    1.7086   39.8152
-#> 8:    85.1605   -3.2190    3.9234    1.7588   41.7476
-#> 9:    84.7745   -3.2389    3.7361    1.6708   41.8512
-#> 10:    84.6549   -3.2078    3.5493    1.6489   41.6110
-#> 11:    84.4739   -3.2788    3.3718    1.5664   42.0076
-#> 12:    84.7871   -3.2674    3.4931    1.6097   40.9060
-#> 13:    84.5267   -3.2635    3.3185    1.6352   39.6914
-#> 14:    84.9806   -3.2353    3.1525    1.6470   39.2556
-#> 15:    84.9752   -3.2566    2.9949    1.6756   39.6152
-#> 16:    85.6293   -3.2232    2.8452    1.7076   39.4391
-#> 17:    85.9944   -3.2268    2.7029    1.6702   40.2731
-#> 18:    86.2811   -3.2260    2.5678    1.7100   41.4854
-#> 19:    86.2617   -3.2476    2.4489    1.7051   41.3066
-#> 20:    85.7552   -3.2032    3.3323    1.8885   42.2273
-#> 21:    85.6493   -3.2685    3.2317    1.7941   39.4198
-#> 22:    86.0133   -3.2457    4.0910    1.7044   39.0319
-#> 23:    86.1636   -3.2528    4.9399    1.6571   38.6728
-#> 24:    86.3086   -3.1708    7.0791    1.8182   39.6791
-#> 25:    85.7316   -3.2203    6.7252    1.7369   38.3546
-#> 26:    85.3476   -3.2341    6.3889    1.6864   38.0521
-#> 27:    85.6328   -3.2543    6.0695    1.6945   37.7990
-#> 28:    85.1715   -3.2191    5.7660    1.7898   38.5662
-#> 29:    85.4945   -3.2264    5.4777    1.7007   40.1659
-#> 30:    85.0864   -3.2463    5.2038    1.6156   39.0718
-#> 31:    85.8220   -3.2347    4.9436    1.6115   39.2011
-#> 32:    85.9869   -3.2400    4.6964    1.6818   41.2956
-#> 33:    85.9899   -3.2041    4.4616    1.6606   40.6657
-#> 34:    85.8353   -3.2065    4.2385    1.6868   41.5006
-#> 35:    85.8113   -3.2366    4.0266    1.8261   41.0403
-#> 36:    85.5233   -3.2389    3.8253    1.7348   39.5202
-#> 37:    85.1751   -3.2657    3.6340    1.6948   39.6097
-#> 38:    85.2768   -3.2380    3.4887    1.6820   38.7641
-#> 39:    84.8240   -3.2264    3.3143    1.5979   39.8074
-#> 40:    85.3754   -3.2147    3.1485    1.5810   39.1710
-#> 41:    85.0277   -3.2347    2.9911    1.7061   39.9948
-#> 42:    85.0113   -3.2651    3.1969    1.6208   39.7266
-#> 43:    85.0772   -3.2729    3.0371    1.6160   40.2919
-#> 44:    85.0769   -3.2272    3.3310    1.7321   38.5229
-#> 45:    85.1638   -3.2546    3.1644    1.6968   40.2382
-#> 46:    84.7966   -3.2597    5.0694    1.6816   38.7996
-#> 47:    85.0588   -3.2247    5.9549    1.7452   39.6569
-#> 48:    85.1769   -3.2557    5.6572    1.7441   37.9050
-#> 49:    84.9296   -3.2425    5.3743    1.6729   37.7885
-#> 50:    85.3414   -3.2421    5.1056    1.6646   38.2243
-#> 51:    84.9127   -3.2674    5.8827    1.7180   40.2859
-#> 52:    85.2014   -3.2471    5.5885    1.7318   39.1745
-#> 53:    85.9330   -3.2228    7.2369    1.8328   39.0461
-#> 54:    86.9718   -3.1447    6.9332    1.8404   39.3098
-#> 55:    87.2708   -3.1595    6.6308    1.8049   39.1338
-#> 56:    87.2006   -3.1746    6.2993    1.7541   38.2780
-#> 57:    87.8013   -3.2306    5.9843    1.6664   40.4876
-#> 58:    87.7294   -3.2120    5.6851    1.5831   41.5056
-#> 59:    87.4898   -3.2207    5.4008    1.5039   41.4401
-#> 60:    86.9156   -3.1861    5.1308    1.6408   39.8972
-#> 61:    86.4508   -3.1870    4.8742    1.5935   39.6871
-#> 62:    86.4028   -3.2191    4.6305    1.6267   39.2092
-#> 63:    86.2536   -3.2491    4.5199    1.5617   39.7603
-#> 64:    85.9775   -3.2650    4.2939    1.6077   39.1909
-#> 65:    85.8907   -3.2430    4.0792    1.6729   37.9420
-#> 66:    85.3450   -3.2888    3.8753    1.6201   40.8998
-#> 67:    85.1869   -3.2940    3.6815    1.6157   40.5107
-#> 68:    84.8029   -3.2830    3.4974    1.6040   40.6254
-#> 69:    85.3549   -3.2425    4.4768    1.5238   40.2418
-#> 70:    85.7957   -3.2296    4.2529    1.7175   40.8618
-#> 71:    85.4200   -3.2381    4.0403    1.6695   41.5731
-#> 72:    85.2950   -3.2566    3.8383    1.5998   40.6494
-#> 73:    85.0683   -3.2464    3.6464    1.5576   39.8095
-#> 74:    85.1667   -3.2436    3.4641    1.6383   39.4925
-#> 75:    84.6547   -3.2300    3.7226    1.6656   40.4684
-#> 76:    84.4882   -3.2521    3.6468    1.6035   40.1800
-#> 77:    84.5250   -3.2398    4.1501    1.6827   40.5269
-#> 78:    84.5191   -3.2372    5.5482    1.6309   41.1739
-#> 79:    84.7471   -3.2581    6.0637    1.6259   41.1003
-#> 80:    85.0581   -3.2680    5.7605    1.6841   40.8918
-#> 81:    84.8468   -3.2564    5.4725    1.6475   39.3456
-#> 82:    84.7614   -3.2385    5.1988    1.7550   38.7275
-#> 83:    85.2921   -3.2657    5.9253    1.6672   39.2423
-#> 84:    85.5760   -3.2261    5.6290    1.7505   39.5500
-#> 85:    85.3215   -3.2277    5.5987    1.8027   39.3145
-#> 86:    85.2656   -3.2023    5.3188    1.8024   40.3098
-#> 87:    84.8950   -3.2551    5.0528    1.7123   39.3470
-#> 88:    84.3157   -3.2661    4.8002    1.6267   38.7095
-#> 89:    84.5442   -3.2870    4.5602    1.5892   39.1735
-#> 90:    85.0956   -3.2195    4.8385    1.5796   39.5164
-#> 91:    84.8619   -3.2621    4.5966    1.6889   39.5512
-#> 92:    84.4901   -3.2735    6.1405    1.6704   39.3358
-#> 93:    84.0819   -3.2609    5.8335    1.6130   38.8618
-#> 94:    84.7585   -3.2336    5.5418    1.6301   38.6591
-#> 95:    85.2669   -3.2358    5.2647    1.6619   38.9136
-#> 96:    85.4955   -3.2064    5.0015    1.7673   39.0495
-#> 97:    85.6591   -3.2016    4.7514    1.7046   40.7861
-#> 98:    86.2097   -3.2833    7.4722    1.6413   42.2938
-#> 99:    85.9645   -3.2570    7.7124    1.5592   41.7216
-#> 100:    85.7018   -3.2605    8.2687    1.6798   40.6639
-#> 101:    85.9905   -3.1956   11.0194    1.7017   39.4324
-#> 102:    87.2679   -3.1741   10.4684    1.7063   38.6812
-#> 103:    86.1910   -3.1709    9.9450    1.7151   38.5198
-#> 104:    86.4413   -3.1544    9.4478    1.7123   38.7428
-#> 105:    85.9840   -3.1921   10.6297    1.8135   38.7775
-#> 106:    85.9926   -3.1839   10.0982    1.7228   40.3136
-#> 107:    85.1792   -3.2343    9.5933    1.6367   40.2709
-#> 108:    84.7583   -3.2332    9.1136    1.6907   41.2122
-#> 109:    85.3756   -3.2311    8.6579    1.7307   39.9303
-#> 110:    84.9686   -3.2365    8.2250    1.7221   40.0379
-#> 111:    84.8527   -3.2448    7.8138    1.6775   39.6794
-#> 112:    84.6271   -3.2609    7.4231    1.7321   41.5666
-#> 113:    84.8515   -3.3056    7.2514    1.7001   41.9758
-#> 114:    84.5991   -3.2319    7.8463    1.7690   41.1386
-#> 115:    85.0535   -3.2864    7.4540    1.7282   40.3883
-#> 116:    85.8661   -3.2355    7.0813    1.7801   39.3078
-#> 117:    85.9911   -3.2357    6.7272    1.6911   38.3913
-#> 118:    86.1894   -3.2424    6.3909    1.6701   38.1915
-#> 119:    85.5637   -3.1992    6.0713    1.7360   38.9386
-#> 120:    86.0733   -3.2069    5.7677    1.7185   36.5189
-#> 121:    86.0168   -3.2181    5.4794    1.7135   38.4044
-#> 122:    86.7470   -3.2319    6.1989    1.6840   38.2615
-#> 123:    86.2918   -3.2089    5.8890    1.6656   38.8486
-#> 124:    85.9387   -3.2124    5.5945    1.6334   37.9425
-#> 125:    86.1519   -3.2717    5.3148    1.7094   38.9708
-#> 126:    85.5194   -3.2391    5.4217    1.6799   39.4876
-#> 127:    85.9691   -3.2205    5.8051    1.6436   40.0593
-#> 128:    85.6171   -3.2309    5.5148    1.6852   39.5398
-#> 129:    84.9252   -3.2495    5.2391    1.7154   40.4020
-#> 130:    85.1496   -3.2882    5.0538    1.7189   40.0908
-#> 131:    85.8552   -3.2474    7.1203    1.6329   39.0547
-#> 132:    86.4666   -3.2151    6.7643    1.7342   38.6596
-#> 133:    86.1550   -3.1895    6.4261    1.7904   38.6211
-#> 134:    86.5040   -3.1785    6.1048    1.7180   39.0804
-#> 135:    85.9752   -3.2116    5.7996    1.6979   38.1745
-#> 136:    86.2161   -3.2075    5.5096    1.7408   38.9002
-#> 137:    85.8408   -3.2604    6.9319    1.7616   39.1657
-#> 138:    86.1261   -3.2179    7.0802    1.8115   37.6614
-#> 139:    85.9082   -3.2374    6.7262    1.7209   38.1986
-#> 140:    85.9556   -3.2641    6.3899    1.8300   39.2071
-#> 141:    86.2052   -3.1928    6.0704    1.7385   38.1745
-#> 142:    86.4062   -3.2076    5.8348    1.6693   38.0271
-#> 143:    86.0680   -3.2372    5.5431    1.7259   39.3885
-#> 144:    86.2001   -3.2040    5.2659    1.6803   38.1606
-#> 145:    86.5820   -3.2306    5.0026    1.6063   38.7208
-#> 146:    86.4522   -3.2072    4.7525    1.6572   37.5206
-#> 147:    85.8311   -3.2320    4.5149    1.7043   39.6955
-#> 148:    86.0754   -3.2072    5.4070    1.6707   38.8858
-#> 149:    87.0038   -3.1954    5.1367    1.7361   37.9862
-#> 150:    86.8647   -3.1903    4.8798    1.7995   39.6906
-#> 151:    86.4913   -3.2101    4.6358    1.7618   39.2462
-#> 152:    86.4667   -3.2254    4.6929    1.7762   38.0665
-#> 153:    86.0176   -3.2241    4.4586    1.7708   37.6367
-#> 154:    85.8680   -3.2359    5.2401    1.7272   37.7322
-#> 155:    85.6560   -3.2147    3.3340    1.7833   38.4605
-#> 156:    85.6927   -3.1987    1.9644    1.8176   39.4958
-#> 157:    86.3686   -3.2294    3.4959    1.6556   39.7058
-#> 158:    86.7614   -3.2051    2.3005    1.6413   40.3968
-#> 159:    86.6393   -3.2243    1.7824    1.6521   40.0846
-#> 160:    86.8686   -3.1850    1.6490    1.7211   39.6362
-#> 161:    86.7853   -3.2071    1.1720    1.6132   39.6921
-#> 162:    86.7337   -3.1825    1.0646    1.5897   41.1027
-#> 163:    86.9192   -3.1365    1.0339    1.6656   40.2410
-#> 164:    86.6652   -3.2052    0.9750    1.5817   40.6189
-#> 165:    86.6154   -3.1870    1.2602    1.6559   40.1832
-#> 166:    86.7300   -3.2096    1.2144    1.6571   39.8989
-#> 167:    86.4536   -3.2135    0.5155    1.7436   39.6313
-#> 168:    86.4848   -3.2315    0.5060    1.6681   39.1479
-#> 169:    86.2641   -3.2444    0.3935    1.6781   40.2903
-#> 170:    86.2482   -3.2628    0.3342    1.6177   40.2600
-#> 171:    86.2833   -3.2338    0.1701    1.6698   39.8946
-#> 172:    86.2155   -3.2175    0.1858    1.6090   39.9709
-#> 173:    86.2916   -3.2313    0.2088    1.6918   41.4421
-#> 174:    86.1920   -3.2050    0.2067    1.7521   40.7724
-#> 175:    86.2771   -3.2071    0.2213    1.5502   40.5055
-#> 176:    86.2589   -3.1867    0.2010    1.5814   40.0963
-#> 177:    86.2740   -3.2209    0.2679    1.6774   40.9479
-#> 178:    86.2210   -3.1896    0.4420    1.5512   40.3238
-#> 179:    86.1769   -3.2036    0.5592    1.6008   40.3873
-#> 180:    85.9366   -3.2046    0.5056    1.6948   41.4254
-#> 181:    85.9173   -3.2167    0.6033    1.6886   39.5784
-#> 182:    85.7077   -3.2508    0.5008    1.7501   40.4224
-#> 183:    85.8084   -3.2743    0.5737    1.7174   40.0576
-#> 184:    85.7776   -3.2518    0.7164    1.7495   39.8748
-#> 185:    85.6192   -3.2378    1.1401    1.7562   39.9841
-#> 186:    85.6951   -3.2460    1.5642    1.7330   39.1282
-#> 187:    85.5281   -3.2309    1.5452    1.7900   38.4833
-#> 188:    85.3476   -3.2018    1.1385    1.8106   39.2842
-#> 189:    85.1914   -3.2180    1.0465    1.7562   40.0715
-#> 190:    85.2759   -3.2275    1.0437    1.7160   39.9928
-#> 191:    85.3630   -3.2728    1.5672    1.7394   39.4749
-#> 192:    85.1334   -3.2467    0.9598    1.6243   39.7385
-#> 193:    84.9313   -3.2401    0.6441    1.6518   39.5447
-#> 194:    84.9097   -3.2361    0.4275    1.6509   40.3383
-#> 195:    84.9131   -3.2241    0.3344    1.5868   39.1438
-#> 196:    84.9117   -3.2419    0.2435    1.6882   40.1132
-#> 197:    84.9569   -3.2776    0.2352    1.6351   40.1070
-#> 198:    84.9113   -3.2334    0.2133    1.6282   39.9988
-#> 199:    84.9028   -3.2637    0.1859    1.6127   38.8695
-#> 200:    84.9020   -3.2456    0.2429    1.6172   40.2644
-#> 201:    84.9327   -3.2292    0.1787    1.6720   40.5826
-#> 202:    84.9313   -3.2363    0.1487    1.6641   40.1952
-#> 203:    84.9208   -3.2350    0.1445    1.6449   40.0176
-#> 204:    84.9312   -3.2296    0.1488    1.6292   40.1353
-#> 205:    84.9302   -3.2277    0.1454    1.6167   40.4137
-#> 206:    84.9378   -3.2314    0.1474    1.6263   40.2241
-#> 207:    84.9190   -3.2369    0.1454    1.6374   40.1459
-#> 208:    84.9085   -3.2385    0.1527    1.6439   40.1931
-#> 209:    84.8920   -3.2411    0.1566    1.6396   40.1558
-#> 210:    84.8787   -3.2435    0.1574    1.6381   40.1872
-#> 211:    84.8784   -3.2460    0.1528    1.6407   40.1825
-#> 212:    84.8745   -3.2469    0.1474    1.6439   40.0865
-#> 213:    84.8702   -3.2474    0.1429    1.6459   40.0164
-#> 214:    84.8592   -3.2476    0.1421    1.6506   39.9852
-#> 215:    84.8558   -3.2479    0.1389    1.6549   39.9882
-#> 216:    84.8542   -3.2488    0.1365    1.6625   39.9461
-#> 217:    84.8594   -3.2488    0.1354    1.6691   39.9751
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-#> 223:    84.8765   -3.2490    0.1296    1.6785   39.8138
-#> 224:    84.8750   -3.2492    0.1274    1.6772   39.8278
-#> 225:    84.8767   -3.2493    0.1266    1.6727   39.8642
-#> 226:    84.8741   -3.2495    0.1251    1.6711   39.8208
-#> 227:    84.8678   -3.2502    0.1234    1.6680   39.8193
-#> 228:    84.8618   -3.2509    0.1217    1.6660   39.7846
-#> 229:    84.8567   -3.2504    0.1208    1.6640   39.7538
-#> 230:    84.8559   -3.2503    0.1215    1.6624   39.7184
-#> 231:    84.8548   -3.2501    0.1203    1.6596   39.6840
-#> 232:    84.8528   -3.2505    0.1206    1.6550   39.6882
-#> 233:    84.8510   -3.2499    0.1229    1.6560   39.7083
-#> 234:    84.8479   -3.2502    0.1243    1.6568   39.7116
-#> 235:    84.8443   -3.2509    0.1244    1.6571   39.7504
-#> 236:    84.8391   -3.2515    0.1253    1.6584   39.7761
-#> 237:    84.8390   -3.2522    0.1246    1.6595   39.8188
-#> 238:    84.8433   -3.2520    0.1240    1.6606   39.8393
-#> 239:    84.8453   -3.2517    0.1233    1.6604   39.8360
-#> 240:    84.8439   -3.2519    0.1225    1.6597   39.8355
-#> 241:    84.8423   -3.2516    0.1215    1.6591   39.8154
-#> 242:    84.8403   -3.2521    0.1208    1.6572   39.7956
-#> 243:    84.8378   -3.2514    0.1199    1.6579   39.7842
-#> 244:    84.8375   -3.2501    0.1191    1.6582   39.7851
-#> 245:    84.8367   -3.2497    0.1200    1.6571   39.7873
-#> 246:    84.8348   -3.2499    0.1200    1.6561   39.7972
-#> 247:    84.8344   -3.2490    0.1196    1.6546   39.8425
-#> 248:    84.8320   -3.2485    0.1197    1.6551   39.8607
-#> 249:    84.8330   -3.2477    0.1212    1.6550   39.8643
-#> 250:    84.8348   -3.2481    0.1217    1.6561   39.8570
-#> 251:    84.8384   -3.2483    0.1214    1.6569   39.8535
-#> 252:    84.8394   -3.2487    0.1218    1.6578   39.8584
-#> 253:    84.8408   -3.2490    0.1229    1.6586   39.9146
-#> 254:    84.8414   -3.2497    0.1232    1.6602   39.9561
-#> 255:    84.8424   -3.2502    0.1229    1.6617   39.9734
-#> 256:    84.8428   -3.2506    0.1230    1.6609   39.9959
-#> 257:    84.8425   -3.2507    0.1221    1.6600   40.0029
-#> 258:    84.8420   -3.2513    0.1213    1.6585   40.0135
-#> 259:    84.8411   -3.2512    0.1212    1.6576   40.0261
-#> 260:    84.8404   -3.2513    0.1219    1.6562   40.0238
-#> 261:    84.8382   -3.2514    0.1226    1.6553   40.0140
-#> 262:    84.8358   -3.2511    0.1226    1.6547   40.0022
-#> 263:    84.8337   -3.2513    0.1224    1.6539   40.0037
-#> 264:    84.8318   -3.2511    0.1223    1.6531   39.9986
-#> 265:    84.8316   -3.2504    0.1213    1.6533   40.0094
-#> 266:    84.8325   -3.2503    0.1202    1.6549   40.0179
-#> 267:    84.8328   -3.2501    0.1189    1.6547   40.0438
-#> 268:    84.8324   -3.2505    0.1183    1.6532   40.0734
-#> 269:    84.8315   -3.2505    0.1177    1.6545   40.0714
-#> 270:    84.8304   -3.2508    0.1175    1.6545   40.0698
-#> 271:    84.8293   -3.2512    0.1173    1.6542   40.0623
-#> 272:    84.8279   -3.2512    0.1165    1.6537   40.0659
-#> 273:    84.8260   -3.2512    0.1171    1.6536   40.0580
-#> 274:    84.8241   -3.2512    0.1172    1.6523   40.0540
-#> 275:    84.8245   -3.2508    0.1171    1.6529   40.0513
-#> 276:    84.8240   -3.2510    0.1165    1.6523   40.0407
-#> 277:    84.8240   -3.2509    0.1160    1.6516   40.0290
-#> 278:    84.8250   -3.2507    0.1156    1.6505   40.0255
-#> 279:    84.8253   -3.2507    0.1147    1.6509   40.0301
-#> 280:    84.8252   -3.2507    0.1140    1.6503   40.0278
-#> 281:    84.8255   -3.2508    0.1135    1.6504   40.0238
-#> 282:    84.8246   -3.2506    0.1128    1.6505   40.0212
-#> 283:    84.8237   -3.2508    0.1120    1.6509   40.0206
-#> 284:    84.8235   -3.2507    0.1121    1.6518   40.0316
-#> 285:    84.8236   -3.2499    0.1121    1.6523   40.0330
-#> 286:    84.8230   -3.2490    0.1118    1.6530   40.0435
-#> 287:    84.8222   -3.2485    0.1119    1.6526   40.0428
-#> 288:    84.8211   -3.2486    0.1120    1.6512   40.0446
-#> 289:    84.8196   -3.2490    0.1121    1.6508   40.0355
-#> 290:    84.8189   -3.2494    0.1121    1.6503   40.0319
-#> 291:    84.8183   -3.2495    0.1126    1.6501   40.0263
-#> 292:    84.8174   -3.2496    0.1127    1.6495   40.0226
-#> 293:    84.8163   -3.2499    0.1126    1.6488   40.0255
-#> 294:    84.8165   -3.2499    0.1125    1.6479   40.0207
-#> 295:    84.8165   -3.2502    0.1130    1.6466   40.0406
-#> 296:    84.8158   -3.2508    0.1131    1.6464   40.0428
-#> 297:    84.8162   -3.2506    0.1129    1.6465   40.0432
-#> 298:    84.8166   -3.2501    0.1131    1.6460   40.0415
-#> 299:    84.8184   -3.2499    0.1138    1.6451   40.0513
-#> 300:    84.8205   -3.2499    0.1144    1.6450   40.0615
-#> 301:    84.8216   -3.2496    0.1156    1.6450   40.0591
-#> 302:    84.8225   -3.2498    0.1161    1.6448   40.0618
-#> 303:    84.8232   -3.2493    0.1163    1.6451   40.0612
-#> 304:    84.8233   -3.2488    0.1166    1.6450   40.0669
-#> 305:    84.8230   -3.2485    0.1163    1.6439   40.0714
-#> 306:    84.8221   -3.2482    0.1158    1.6440   40.0838
-#> 307:    84.8217   -3.2479    0.1154    1.6445   40.0835
-#> 308:    84.8219   -3.2477    0.1156    1.6450   40.0829
-#> 309:    84.8224   -3.2477    0.1152    1.6450   40.0836
-#> 310:    84.8224   -3.2480    0.1148    1.6457   40.0873
-#> 311:    84.8225   -3.2480    0.1143    1.6459   40.0894
-#> 312:    84.8219   -3.2482    0.1136    1.6460   40.0835
-#> 313:    84.8214   -3.2484    0.1131    1.6462   40.0810
-#> 314:    84.8208   -3.2485    0.1130    1.6471   40.0786
-#> 315:    84.8211   -3.2485    0.1128    1.6470   40.0707
-#> 316:    84.8211   -3.2483    0.1127    1.6469   40.0628
-#> 317:    84.8210   -3.2482    0.1124    1.6472   40.0580
-#> 318:    84.8201   -3.2484    0.1122    1.6472   40.0602
-#> 319:    84.8196   -3.2484    0.1117    1.6479   40.0555
-#> 320:    84.8183   -3.2480    0.1119    1.6486   40.0659
-#> 321:    84.8173   -3.2479    0.1122    1.6489   40.0713
-#> 322:    84.8164   -3.2479    0.1129    1.6491   40.0781
-#> 323:    84.8159   -3.2480    0.1136    1.6489   40.0790
-#> 324:    84.8158   -3.2480    0.1140    1.6489   40.0746
-#> 325:    84.8158   -3.2480    0.1138    1.6484   40.0845
-#> 326:    84.8157   -3.2482    0.1137    1.6482   40.0953
-#> 327:    84.8155   -3.2482    0.1134    1.6482   40.0955
-#> 328:    84.8156   -3.2482    0.1133    1.6471   40.1167
-#> 329:    84.8152   -3.2483    0.1129    1.6466   40.1195
-#> 330:    84.8152   -3.2482    0.1124    1.6459   40.1280
-#> 331:    84.8151   -3.2478    0.1120    1.6467   40.1282
-#> 332:    84.8147   -3.2477    0.1115    1.6471   40.1265
-#> 333:    84.8145   -3.2477    0.1110    1.6470   40.1333
-#> 334:    84.8144   -3.2479    0.1108    1.6468   40.1474
-#> 335:    84.8141   -3.2481    0.1106    1.6475   40.1549
-#> 336:    84.8135   -3.2481    0.1103    1.6481   40.1664
-#> 337:    84.8134   -3.2481    0.1106    1.6476   40.1837
-#> 338:    84.8129   -3.2479    0.1109    1.6482   40.1855
-#> 339:    84.8126   -3.2478    0.1107    1.6478   40.1830
-#> 340:    84.8120   -3.2482    0.1106    1.6471   40.1893
-#> 341:    84.8120   -3.2482    0.1106    1.6467   40.1931
-#> 342:    84.8119   -3.2482    0.1106    1.6473   40.2091
-#> 343:    84.8135   -3.2483    0.1109    1.6475   40.2113
-#> 344:    84.8153   -3.2483    0.1114    1.6472   40.2116
-#> 345:    84.8165   -3.2484    0.1119    1.6465   40.2110
-#> 346:    84.8171   -3.2481    0.1121    1.6462   40.2099
-#> 347:    84.8184   -3.2483    0.1126    1.6459   40.2120
-#> 348:    84.8189   -3.2483    0.1127    1.6455   40.2115
-#> 349:    84.8198   -3.2483    0.1127    1.6450   40.2087
-#> 350:    84.8202   -3.2482    0.1125    1.6454   40.2118
-#> 351:    84.8208   -3.2483    0.1120    1.6447   40.2094
-#> 352:    84.8213   -3.2483    0.1118    1.6444   40.2070
-#> 353:    84.8218   -3.2481    0.1115    1.6445   40.2077
-#> 354:    84.8226   -3.2482    0.1114    1.6439   40.2077
-#> 355:    84.8230   -3.2481    0.1113    1.6439   40.2072
-#> 356:    84.8232   -3.2479    0.1111    1.6439   40.2075
-#> 357:    84.8239   -3.2477    0.1109    1.6441   40.2021
-#> 358:    84.8245   -3.2476    0.1107    1.6445   40.2028
-#> 359:    84.8251   -3.2476    0.1107    1.6452   40.2032
-#> 360:    84.8252   -3.2474    0.1110    1.6462   40.2012
-#> 361:    84.8258   -3.2473    0.1108    1.6469   40.2043
-#> 362:    84.8260   -3.2475    0.1107    1.6467   40.2056
-#> 363:    84.8262   -3.2474    0.1106    1.6469   40.2028
-#> 364:    84.8266   -3.2472    0.1104    1.6473   40.1979
-#> 365:    84.8270   -3.2469    0.1102    1.6479   40.1923
-#> 366:    84.8273   -3.2469    0.1100    1.6482   40.1872
-#> 367:    84.8267   -3.2468    0.1099    1.6483   40.1836
-#> 368:    84.8263   -3.2470    0.1099    1.6483   40.1850
-#> 369:    84.8269   -3.2471    0.1098    1.6484   40.1864
-#> 370:    84.8274   -3.2472    0.1098    1.6484   40.1856
-#> 371:    84.8282   -3.2471    0.1101    1.6489   40.1839
-#> 372:    84.8288   -3.2469    0.1099    1.6492   40.1804
-#> 373:    84.8294   -3.2467    0.1098    1.6494   40.1806
-#> 374:    84.8301   -3.2466    0.1096    1.6491   40.1855
-#> 375:    84.8301   -3.2467    0.1093    1.6488   40.1951
-#> 376:    84.8302   -3.2467    0.1092    1.6484   40.1921
-#> 377:    84.8302   -3.2467    0.1092    1.6486   40.1842
-#> 378:    84.8300   -3.2467    0.1095    1.6485   40.1760
-#> 379:    84.8296   -3.2468    0.1094    1.6483   40.1701
-#> 380:    84.8297   -3.2469    0.1094    1.6483   40.1738
-#> 381:    84.8299   -3.2469    0.1093    1.6485   40.1801
-#> 382:    84.8302   -3.2470    0.1092    1.6488   40.1857
-#> 383:    84.8299   -3.2469    0.1090    1.6491   40.1859
-#> 384:    84.8297   -3.2470    0.1090    1.6488   40.1903
-#> 385:    84.8289   -3.2469    0.1095    1.6487   40.1978
-#> 386:    84.8282   -3.2470    0.1098    1.6487   40.1976
-#> 387:    84.8277   -3.2471    0.1101    1.6488   40.1910
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-#> 390:    84.8259   -3.2472    0.1109    1.6491   40.1881
-#> 391:    84.8250   -3.2472    0.1111    1.6499   40.1919
-#> 392:    84.8248   -3.2471    0.1113    1.6501   40.1961
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-#> 394:    84.8241   -3.2470    0.1114    1.6508   40.1933
-#> 395:    84.8239   -3.2469    0.1115    1.6510   40.1916
-#> 396:    84.8239   -3.2468    0.1115    1.6515   40.1946
-#> 397:    84.8239   -3.2466    0.1113    1.6517   40.1979
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-#> 399:    84.8244   -3.2466    0.1112    1.6522   40.1975
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-#> 403:    84.8257   -3.2470    0.1109    1.6524   40.1787
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-#> 407:    84.8231   -3.2471    0.1112    1.6531   40.1742
-#> 408:    84.8229   -3.2471    0.1110    1.6530   40.1728
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-#> 419:    84.8231   -3.2476    0.1114    1.6513   40.1921
-#> 420:    84.8226   -3.2477    0.1113    1.6511   40.1880
-#> 421:    84.8220   -3.2478    0.1111    1.6508   40.1859
-#> 422:    84.8213   -3.2478    0.1110    1.6503   40.1897
-#> 423:    84.8207   -3.2479    0.1110    1.6499   40.1876
-#> 424:    84.8203   -3.2479    0.1111    1.6498   40.1860
-#> 425:    84.8198   -3.2479    0.1111    1.6498   40.1817
-#> 426:    84.8191   -3.2479    0.1113    1.6498   40.1796
-#> 427:    84.8186   -3.2478    0.1112    1.6498   40.1781
-#> 428:    84.8183   -3.2478    0.1114    1.6496   40.1738
-#> 429:    84.8177   -3.2477    0.1116    1.6495   40.1695
-#> 430:    84.8172   -3.2477    0.1119    1.6496   40.1739
-#> 431:    84.8169   -3.2478    0.1120    1.6494   40.1741
-#> 432:    84.8169   -3.2479    0.1121    1.6490   40.1758
-#> 433:    84.8170   -3.2479    0.1121    1.6491   40.1793
-#> 434:    84.8171   -3.2480    0.1122    1.6488   40.1808
-#> 435:    84.8173   -3.2481    0.1123    1.6487   40.1845
-#> 436:    84.8176   -3.2481    0.1123    1.6489   40.1866
-#> 437:    84.8178   -3.2480    0.1122    1.6496   40.1872
-#> 438:    84.8183   -3.2480    0.1121    1.6502   40.1869
-#> 439:    84.8185   -3.2481    0.1119    1.6504   40.1834
-#> 440:    84.8185   -3.2480    0.1118    1.6506   40.1831
-#> 441:    84.8188   -3.2480    0.1120    1.6502   40.1893
-#> 442:    84.8192   -3.2480    0.1120    1.6501   40.1930
-#> 443:    84.8196   -3.2480    0.1120    1.6499   40.1917
-#> 444:    84.8202   -3.2478    0.1122    1.6498   40.1966
-#> 445:    84.8207   -3.2476    0.1124    1.6499   40.1977
-#> 446:    84.8210   -3.2473    0.1123    1.6496   40.2017
-#> 447:    84.8217   -3.2472    0.1123    1.6491   40.2030
-#> 448:    84.8221   -3.2473    0.1122    1.6488   40.2025
-#> 449:    84.8225   -3.2474    0.1121    1.6485   40.2069
-#> 450:    84.8224   -3.2473    0.1119    1.6484   40.2078
-#> 451:    84.8221   -3.2473    0.1118    1.6483   40.2032
-#> 452:    84.8220   -3.2472    0.1117    1.6484   40.1989
-#> 453:    84.8220   -3.2472    0.1117    1.6483   40.1953
-#> 454:    84.8220   -3.2473    0.1122    1.6483   40.1942
-#> 455:    84.8220   -3.2472    0.1124    1.6484   40.1932
-#> 456:    84.8220   -3.2470    0.1124    1.6478   40.1972
-#> 457:    84.8222   -3.2469    0.1125    1.6476   40.1989
-#> 458:    84.8226   -3.2468    0.1125    1.6479   40.1989
-#> 459:    84.8228   -3.2467    0.1126    1.6480   40.2035
-#> 460:    84.8231   -3.2467    0.1124    1.6479   40.2032
-#> 461:    84.8236   -3.2466    0.1126    1.6482   40.2030
-#> 462:    84.8238   -3.2466    0.1124    1.6481   40.2052
-#> 463:    84.8238   -3.2467    0.1123    1.6479   40.2023
-#> 464:    84.8233   -3.2467    0.1123    1.6479   40.2004
-#> 465:    84.8230   -3.2468    0.1123    1.6482   40.2043
-#> 466:    84.8233   -3.2469    0.1123    1.6480   40.2062
-#> 467:    84.8236   -3.2468    0.1121    1.6480   40.2026
-#> 468:    84.8238   -3.2468    0.1120    1.6477   40.2034
-#> 469:    84.8239   -3.2468    0.1119    1.6474   40.2035
-#> 470:    84.8241   -3.2469    0.1116    1.6473   40.2015
-#> 471:    84.8241   -3.2470    0.1116    1.6476   40.1993
-#> 472:    84.8240   -3.2469    0.1117    1.6478   40.1977
-#> 473:    84.8239   -3.2468    0.1119    1.6479   40.1949
-#> 474:    84.8239   -3.2466    0.1118    1.6480   40.1946
-#> 475:    84.8239   -3.2464    0.1119    1.6483   40.1941
-#> 476:    84.8237   -3.2462    0.1121    1.6488   40.1930
-#> 477:    84.8235   -3.2462    0.1122    1.6488   40.1901
-#> 478:    84.8235   -3.2462    0.1125    1.6488   40.1837
-#> 479:    84.8238   -3.2463    0.1128    1.6486   40.1814
-#> 480:    84.8238   -3.2464    0.1129    1.6484   40.1794
-#> 481:    84.8239   -3.2464    0.1129    1.6483   40.1783
-#> 482:    84.8237   -3.2465    0.1130    1.6482   40.1784
-#> 483:    84.8234   -3.2465    0.1130    1.6483   40.1764
-#> 484:    84.8227   -3.2465    0.1132    1.6482   40.1775
-#> 485:    84.8223   -3.2465    0.1133    1.6483   40.1764
-#> 486:    84.8219   -3.2465    0.1135    1.6484   40.1781
-#> 487:    84.8215   -3.2465    0.1136    1.6487   40.1770
-#> 488:    84.8214   -3.2466    0.1136    1.6486   40.1796
-#> 489:    84.8214   -3.2466    0.1134    1.6489   40.1801
-#> 490:    84.8214   -3.2466    0.1132    1.6490   40.1786
-#> 491:    84.8218   -3.2466    0.1131    1.6494   40.1805
-#> 492:    84.8220   -3.2465    0.1133    1.6495   40.1805
-#> 493:    84.8223   -3.2465    0.1137    1.6493   40.1791
-#> 494:    84.8223   -3.2465    0.1140    1.6494   40.1774
-#> 495:    84.8224   -3.2465    0.1142    1.6491   40.1764
-#> 496:    84.8225   -3.2465    0.1142    1.6491   40.1750
-#> 497:    84.8229   -3.2465    0.1142    1.6487   40.1742
-#> 498:    84.8230   -3.2466    0.1140    1.6485   40.1712
-#> 499:    84.8229   -3.2466    0.1137    1.6485   40.1688
-#> 500:    84.8228   -3.2468    0.1134    1.6488   40.1690
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |log_k_parent |     sigma |        o1 |
-#> |.....................|        o2 |...........|...........|...........|
-#> |    1|     451.22394 |     1.000 |    -1.000 |   -0.7995 |   -0.9125 |
-#> |.....................|   -0.9081 |...........|...........|...........|
-#> |    U|     451.22394 |     86.39 |    -3.215 |     5.768 |    0.7049 |
-#> |.....................|    0.9021 |...........|...........|...........|
-#> |    X|     451.22394 |     86.39 |   0.04015 |     5.768 |    0.7049 |
-#> |.....................|    0.9021 |...........|...........|...........|
-#> |    G|    Gill Diff. |     52.79 |   0.01520 |    -15.05 |    0.6163 |
-#> |.....................|     2.488 |...........|...........|...........|
-#> |    2|     3099.6543 |   0.03939 |    -1.000 |   -0.5255 |   -0.9237 |
-#> |.....................|   -0.9534 |...........|...........|...........|
-#> |    U|     3099.6543 |     3.403 |    -3.215 |     6.558 |    0.6970 |
-#> |.....................|    0.8613 |...........|...........|...........|
-#> |    X|     3099.6543 |     3.403 |   0.04014 |     6.558 |    0.6970 |
-#> |.....................|    0.8613 |...........|...........|...........|
-#> |    3|     473.10068 |    0.9039 |    -1.000 |   -0.7721 |   -0.9136 |
-#> |.....................|   -0.9126 |...........|...........|...........|
-#> |    U|     473.10068 |     78.09 |    -3.215 |     5.847 |    0.7041 |
-#> |.....................|    0.8980 |...........|...........|...........|
-#> |    X|     473.10068 |     78.09 |   0.04015 |     5.847 |    0.7041 |
-#> |.....................|    0.8980 |...........|...........|...........|
-#> |    4|     450.95086 |    0.9904 |    -1.000 |   -0.7967 |   -0.9126 |
-#> |.....................|   -0.9086 |...........|...........|...........|
-#> |    U|     450.95086 |     85.56 |    -3.215 |     5.776 |    0.7048 |
-#> |.....................|    0.9017 |...........|...........|...........|
-#> |    X|     450.95086 |     85.56 |   0.04015 |     5.776 |    0.7048 |
-#> |.....................|    0.9017 |...........|...........|...........|
-#> |    F| Forward Diff. |    -4.520 |   0.09729 |    -14.85 |   -0.2941 |
-#> |.....................|     2.449 |...........|...........|...........|
-#> |    5|     450.82239 |    0.9932 |    -1.000 |   -0.7873 |   -0.9124 |
-#> |.....................|   -0.9101 |...........|...........|...........|
-#> |    U|     450.82239 |     85.81 |    -3.215 |     5.804 |    0.7049 |
-#> |.....................|    0.9003 |...........|...........|...........|
-#> |    X|     450.82239 |     85.81 |   0.04015 |     5.804 |    0.7049 |
-#> |.....................|    0.9003 |...........|...........|...........|
-#> |    6|     450.73959 |    0.9981 |    -1.000 |   -0.7712 |   -0.9121 |
-#> |.....................|   -0.9128 |...........|...........|...........|
-#> |    U|     450.73959 |     86.23 |    -3.215 |     5.850 |    0.7051 |
-#> |.....................|    0.8979 |...........|...........|...........|
-#> |    X|     450.73959 |     86.23 |   0.04015 |     5.850 |    0.7051 |
-#> |.....................|    0.8979 |...........|...........|...........|
-#> |    F| Forward Diff. |     41.55 |   0.02901 |    -12.22 |    0.2553 |
-#> |.....................|     2.069 |...........|...........|...........|
-#> |    7|     450.34694 |    0.9875 |    -1.000 |   -0.7467 |   -0.9114 |
-#> |.....................|   -0.9169 |...........|...........|...........|
-#> |    U|     450.34694 |     85.32 |    -3.215 |     5.921 |    0.7056 |
-#> |.....................|    0.8942 |...........|...........|...........|
-#> |    X|     450.34694 |     85.32 |   0.04014 |     5.921 |    0.7056 |
-#> |.....................|    0.8942 |...........|...........|...........|
-#> |    F| Forward Diff. |    -19.58 |    0.1161 |    -10.02 |   -0.6042 |
-#> |.....................|     1.700 |...........|...........|...........|
-#> |    8|     450.09191 |    0.9931 |    -1.001 |   -0.7208 |   -0.9093 |
-#> |.....................|   -0.9217 |...........|...........|...........|
-#> |    U|     450.09191 |     85.80 |    -3.216 |     5.995 |    0.7071 |
-#> |.....................|    0.8899 |...........|...........|...........|
-#> |    X|     450.09191 |     85.80 |   0.04012 |     5.995 |    0.7071 |
-#> |.....................|    0.8899 |...........|...........|...........|
-#> |    F| Forward Diff. |     13.00 |   0.06566 |    -7.570 |   -0.3896 |
-#> |.....................|     1.273 |...........|...........|...........|
-#> |    9|     449.93949 |    0.9873 |    -1.002 |   -0.6965 |   -0.8998 |
-#> |.....................|   -0.9259 |...........|...........|...........|
-#> |    U|     449.93949 |     85.30 |    -3.217 |     6.065 |    0.7138 |
-#> |.....................|    0.8861 |...........|...........|...........|
-#> |    X|     449.93949 |     85.30 |   0.04009 |     6.065 |    0.7138 |
-#> |.....................|    0.8861 |...........|...........|...........|
-#> |    F| Forward Diff. |    -18.86 |    0.1073 |    -5.670 |   -0.6860 |
-#> |.....................|    0.8878 |...........|...........|...........|
-#> |   10|     449.82026 |    0.9918 |    -1.004 |   -0.6799 |   -0.8791 |
-#> |.....................|   -0.9254 |...........|...........|...........|
-#> |    U|     449.82026 |     85.69 |    -3.219 |     6.113 |    0.7284 |
-#> |.....................|    0.8865 |...........|...........|...........|
-#> |    X|     449.82026 |     85.69 |   0.04000 |     6.113 |    0.7284 |
-#> |.....................|    0.8865 |...........|...........|...........|
-#> |    F| Forward Diff. |     8.164 |   0.05669 |    -4.296 |   -0.3775 |
-#> |.....................|    0.8823 |...........|...........|...........|
-#> |   11|     449.76996 |    0.9897 |    -1.006 |   -0.6720 |   -0.8560 |
-#> |.....................|   -0.9364 |...........|...........|...........|
-#> |    U|     449.76996 |     85.50 |    -3.221 |     6.136 |    0.7447 |
-#> |.....................|    0.8766 |...........|...........|...........|
-#> |    X|     449.76996 |     85.50 |   0.03990 |     6.136 |    0.7447 |
-#> |.....................|    0.8766 |...........|...........|...........|
-#> |    F| Forward Diff. |    -2.743 |   0.05613 |    -3.782 |   -0.3486 |
-#> |.....................|  -0.07732 |...........|...........|...........|
-#> |   12|     449.73800 |    0.9901 |    -1.008 |   -0.6600 |   -0.8416 |
-#> |.....................|   -0.9169 |...........|...........|...........|
-#> |    U|       449.738 |     85.54 |    -3.223 |     6.170 |    0.7549 |
-#> |.....................|    0.8942 |...........|...........|...........|
-#> |    X|       449.738 |     85.54 |   0.03983 |     6.170 |    0.7549 |
-#> |.....................|    0.8942 |...........|...........|...........|
-#> |    F| Forward Diff. |    0.5907 |   0.04688 |    -2.910 |   -0.3174 |
-#> |.....................|     1.529 |...........|...........|...........|
-#> |   13|     449.73838 |    0.9854 |    -1.008 |   -0.6366 |   -0.8390 |
-#> |.....................|   -0.9292 |...........|...........|...........|
-#> |    U|     449.73838 |     85.13 |    -3.224 |     6.238 |    0.7567 |
-#> |.....................|    0.8831 |...........|...........|...........|
-#> |    X|     449.73838 |     85.13 |   0.03981 |     6.238 |    0.7567 |
-#> |.....................|    0.8831 |...........|...........|...........|
-#> |   14|     449.71577 |    0.9877 |    -1.008 |   -0.6484 |   -0.8403 |
-#> |.....................|   -0.9231 |...........|...........|...........|
-#> |    U|     449.71577 |     85.33 |    -3.223 |     6.204 |    0.7558 |
-#> |.....................|    0.8886 |...........|...........|...........|
-#> |    X|     449.71577 |     85.33 |   0.03982 |     6.204 |    0.7558 |
-#> |.....................|    0.8886 |...........|...........|...........|
-#> |    F| Forward Diff. |    -13.00 |   0.06593 |    -2.084 |   -0.4341 |
-#> |.....................|     1.007 |...........|...........|...........|
-#> |   15|     449.68436 |    0.9912 |    -1.009 |   -0.6401 |   -0.8344 |
-#> |.....................|   -0.9311 |...........|...........|...........|
-#> |    U|     449.68436 |     85.64 |    -3.224 |     6.228 |    0.7599 |
-#> |.....................|    0.8814 |...........|...........|...........|
-#> |    X|     449.68436 |     85.64 |   0.03979 |     6.228 |    0.7599 |
-#> |.....................|    0.8814 |...........|...........|...........|
-#> |    F| Forward Diff. |     7.939 |   0.02803 |    -1.419 |   -0.2659 |
-#> |.....................|    0.3125 |...........|...........|...........|
-#> |   16|     449.66988 |    0.9896 |    -1.010 |   -0.6363 |   -0.8221 |
-#> |.....................|   -0.9344 |...........|...........|...........|
-#> |    U|     449.66988 |     85.50 |    -3.226 |     6.239 |    0.7686 |
-#> |.....................|    0.8784 |...........|...........|...........|
-#> |    X|     449.66988 |     85.50 |   0.03973 |     6.239 |    0.7686 |
-#> |.....................|    0.8784 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.8695 |   0.03361 |    -1.202 |   -0.2917 |
-#> |.....................|   0.02327 |...........|...........|...........|
-#> |   17|     449.66421 |    0.9900 |    -1.012 |   -0.6343 |   -0.8088 |
-#> |.....................|   -0.9351 |...........|...........|...........|
-#> |    U|     449.66421 |     85.53 |    -3.227 |     6.245 |    0.7779 |
-#> |.....................|    0.8778 |...........|...........|...........|
-#> |    X|     449.66421 |     85.53 |   0.03969 |     6.245 |    0.7779 |
-#> |.....................|    0.8778 |...........|...........|...........|
-#> |   18|     449.65407 |    0.9895 |    -1.015 |   -0.6307 |   -0.7728 |
-#> |.....................|   -0.9370 |...........|...........|...........|
-#> |    U|     449.65407 |     85.49 |    -3.230 |     6.255 |    0.8033 |
-#> |.....................|    0.8761 |...........|...........|...........|
-#> |    X|     449.65407 |     85.49 |   0.03957 |     6.255 |    0.8033 |
-#> |.....................|    0.8761 |...........|...........|...........|
-#> |    F| Forward Diff. |    0.6836 |  0.009868 |   -0.9456 |   -0.1262 |
-#> |.....................|   -0.2597 |...........|...........|...........|
-#> |   19|     449.64227 |    0.9890 |    -1.006 |   -0.6121 |   -0.7274 |
-#> |.....................|   -0.9339 |...........|...........|...........|
-#> |    U|     449.64227 |     85.45 |    -3.222 |     6.309 |    0.8353 |
-#> |.....................|    0.8789 |...........|...........|...........|
-#> |    X|     449.64227 |     85.45 |   0.03989 |     6.309 |    0.8353 |
-#> |.....................|    0.8789 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.4372 |   0.06357 |    0.2445 |  -0.08318 |
-#> |.....................|  -0.05696 |...........|...........|...........|
-#> |   20|     449.64227 |    0.9890 |    -1.006 |   -0.6121 |   -0.7274 |
-#> |.....................|   -0.9339 |...........|...........|...........|
-#> |    U|     449.64227 |     85.45 |    -3.222 |     6.309 |    0.8353 |
-#> |.....................|    0.8789 |...........|...........|...........|
-#> |    X|     449.64227 |     85.45 |   0.03989 |     6.309 |    0.8353 |
-#> |.....................|    0.8789 |...........|...........|...........|
-#> calculating covariance matrix
+#>   no cache: create with `rxCreateCache()`
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei",
+  control = foceiControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> calculating covariance matrix
 #> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo

-f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> 1:    93.6754   -0.2977    2.0254    2.7655    0.7032    0.5111   15.3443
-#> 2:    93.8828   -0.2006    2.0786    2.6886    0.6681    0.4855    7.5256
-#> 3:    94.0494   -0.2006    2.0891    2.9975    0.6347    0.4612    7.0501
-#> 4:    94.1641   -0.2446    2.0103    3.6008    0.6029    0.4382    6.2482
-#> 5:    93.8983   -0.2562    1.9851    4.5637    0.5728    0.4163    6.1507
-#> 6:    93.9311   -0.2542    1.9733    5.7516    0.5441    0.3954    6.1445
-#> 7:    93.8631   -0.2535    1.9876    5.4640    0.5169    0.3757    5.9234
-#> 8:    94.2851   -0.2327    1.9851    5.7884    0.4943    0.3569    5.9887
-#> 9:    94.2114   -0.2348    2.0169    5.4990    0.4733    0.3390    5.9730
-#> 10:    94.0782   -0.1951    2.0678    5.2240    0.4969    0.3221    5.7694
-#> 11:    94.0527   -0.1898    2.0988    4.9628    0.4924    0.3060    5.6429
-#> 12:    93.9845   -0.1795    2.1168    4.7147    0.4748    0.2907    5.4764
-#> 13:    93.9424   -0.1958    2.0924    4.4790    0.4551    0.2762    5.5598
-#> 14:    94.2255   -0.2005    2.0963    4.2910    0.4552    0.2623    5.4520
-#> 15:    94.6065   -0.1964    2.0794    4.0765    0.4516    0.2492    5.5275
-#> 16:    94.8393   -0.1872    2.0825    4.7814    0.4714    0.2368    5.4708
-#> 17:    94.5489   -0.1873    2.0822    5.3772    0.4714    0.2249    5.5790
-#> 18:    94.5797   -0.1994    2.0702    5.1083    0.4563    0.2137    5.5962
-#> 19:    94.7205   -0.1987    2.0942    5.1405    0.4580    0.2030    5.8328
-#> 20:    94.2162   -0.1961    2.0955    7.2352    0.4578    0.2081    5.5730
-#> 21:    94.2688   -0.1935    2.0980    6.8735    0.4539    0.2199    5.6561
-#> 22:    94.4008   -0.2294    2.0430    6.5298    0.4312    0.2528    5.4970
-#> 23:    93.8617   -0.2126    2.0861    6.2033    0.4420    0.2401    5.3679
-#> 24:    93.9223   -0.2173    2.0786    5.8931    0.4419    0.2281    5.4475
-#> 25:    94.1259   -0.2199    2.0790    5.5985    0.4429    0.2167    5.2610
-#> 26:    93.5597   -0.1966    2.1115    5.3186    0.4521    0.2059    5.0971
-#> 27:    93.5468   -0.2077    2.1016    5.0526    0.4458    0.2090    5.2223
-#> 28:    93.6901   -0.2106    2.0884    4.8000    0.4439    0.2114    5.1693
-#> 29:    93.4521   -0.1991    2.1349    4.5600    0.4236    0.2248    5.1834
-#> 30:    93.7678   -0.1998    2.1267    5.5252    0.4212    0.2297    5.0549
-#> 31:    93.5695   -0.2039    2.1244    5.2489    0.4165    0.2334    5.0965
-#> 32:    93.8288   -0.1855    2.1392    5.1872    0.4401    0.2286    5.0321
-#> 33:    93.9053   -0.1827    2.1426    4.9278    0.4479    0.2171    5.0706
-#> 34:    94.0876   -0.1871    2.1151    4.6814    0.4613    0.2063    5.1438
-#> 35:    94.5298   -0.1845    2.1221    4.4474    0.4586    0.2006    5.1897
-#> 36:    94.3221   -0.1765    2.1144    5.3164    0.4401    0.2193    5.0921
-#> 37:    94.3600   -0.1842    2.1021    5.3586    0.4507    0.2210    5.0926
-#> 38:    94.3734   -0.1790    2.1261    5.0907    0.4494    0.2100    5.1494
-#> 39:    94.5052   -0.1806    2.1319    4.8362    0.4514    0.1995    5.0177
-#> 40:    94.1042   -0.1906    2.0983    4.5944    0.4360    0.1984    5.2507
-#> 41:    94.1815   -0.1914    2.1166    4.3646    0.4385    0.1977    5.1065
-#> 42:    93.9837   -0.2144    2.0673    4.1464    0.4378    0.1878    5.1603
-#> 43:    93.8806   -0.2107    2.0840    3.9642    0.4456    0.1848    5.0904
-#> 44:    94.1765   -0.2107    2.0722    3.7660    0.4456    0.1881    5.1562
-#> 45:    94.2089   -0.2018    2.0874    3.5777    0.4482    0.1787    5.1219
-#> 46:    93.8851   -0.2111    2.0869    3.9421    0.4462    0.1697    5.0752
-#> 47:    94.1372   -0.2192    2.0731    3.7450    0.4517    0.1733    5.1784
-#> 48:    94.0436   -0.2157    2.0730    3.5578    0.4577    0.1854    5.1957
-#> 49:    93.9915   -0.2122    2.0740    3.3799    0.4450    0.1829    5.1116
-#> 50:    94.0579   -0.2233    2.0633    3.2109    0.4453    0.1964    5.0295
-#> 51:    94.0044   -0.2283    2.0544    3.9314    0.4563    0.2118    5.0457
-#> 52:    94.1080   -0.2174    2.0551    4.8914    0.4548    0.2182    5.0504
-#> 53:    94.3715   -0.2134    2.0598    6.2569    0.4509    0.2162    4.9574
-#> 54:    94.7344   -0.2119    2.0459    5.9440    0.4563    0.2121    5.1069
-#> 55:    94.2730   -0.2055    2.0625    5.6468    0.4758    0.2125    5.2656
-#> 56:    94.0206   -0.2017    2.0715    5.3645    0.4719    0.2045    5.1400
-#> 57:    94.0409   -0.1986    2.0837    5.0963    0.4801    0.2068    5.0902
-#> 58:    94.2392   -0.2122    2.0652    4.8415    0.4560    0.2334    5.1883
-#> 59:    93.9996   -0.1962    2.0764    4.5994    0.4686    0.2417    5.1242
-#> 60:    94.1448   -0.1840    2.1016    4.3694    0.4916    0.2296    5.0867
-#> 61:    94.4861   -0.1840    2.1239    4.3846    0.4916    0.2181    5.3979
-#> 62:    93.9892   -0.1781    2.1083    5.1623    0.5216    0.2072    5.0944
-#> 63:    94.0641   -0.1822    2.1129    4.9628    0.5123    0.1969    5.4228
-#> 64:    94.1414   -0.1733    2.1343    6.7238    0.5220    0.1879    5.3546
-#> 65:    94.0908   -0.1754    2.1160    8.4197    0.5165    0.1852    5.0873
-#> 66:    94.1490   -0.1753    2.1054    7.9987    0.5183    0.1857    5.0777
-#> 67:    93.8958   -0.1613    2.1295    7.5988    0.5004    0.2102    5.0641
-#> 68:    94.0579   -0.1683    2.1511    7.2188    0.5083    0.2110    5.3362
-#> 69:    94.0001   -0.1581    2.1629    6.8579    0.5225    0.2272    5.4399
-#> 70:    93.9712   -0.1733    2.1393    6.5150    0.5153    0.2403    5.5011
-#> 71:    94.3143   -0.1758    2.0989    6.1893    0.5043    0.2713    5.5366
-#> 72:    94.2138   -0.1842    2.1003    5.8798    0.5130    0.2578    5.2964
-#> 73:    94.1742   -0.1951    2.0773    5.5858    0.5165    0.2449    5.1986
-#> 74:    94.1287   -0.2003    2.0606    5.3065    0.5115    0.2326    4.8815
-#> 75:    94.4113   -0.1918    2.0811    5.6717    0.5153    0.2210    4.8370
-#> 76:    94.5175   -0.1940    2.0773    5.3881    0.5127    0.2127    4.9333
-#> 77:    94.4157   -0.1882    2.0714    5.1187    0.5189    0.2021    5.0162
-#> 78:    94.6190   -0.2000    2.0529    4.8628    0.5057    0.2064    4.9436
-#> 79:    94.8081   -0.2006    2.0458    4.6196    0.5053    0.2177    5.0159
-#> 80:    94.7817   -0.1943    2.0547    4.3886    0.5076    0.2099    5.1427
-#> 81:    94.5410   -0.1990    2.0686    4.8770    0.5032    0.2092    5.1192
-#> 82:    94.9536   -0.1936    2.0879    6.9870    0.4781    0.2068    5.1053
-#> 83:    94.7923   -0.1936    2.0777    6.6377    0.4734    0.2120    5.1233
-#> 84:    94.9314   -0.1881    2.0981    6.3058    0.4701    0.2088    5.2821
-#> 85:    94.8024   -0.1866    2.0975    5.9905    0.4684    0.2150    5.2088
-#> 86:    94.6506   -0.2019    2.0677    5.6910    0.4510    0.2043    5.2488
-#> 87:    94.9460   -0.1868    2.0823    5.4064    0.4625    0.2089    5.2663
-#> 88:    94.6365   -0.1901    2.0791    5.3471    0.4509    0.2203    5.2214
-#> 89:    94.5943   -0.2135    2.0521    5.0798    0.4585    0.2093    5.0161
-#> 90:    94.7957   -0.2131    2.0545    4.8258    0.4502    0.2026    5.1344
-#> 91:    94.6308   -0.2096    2.0565    4.5845    0.4566    0.2108    5.0403
-#> 92:    94.3521   -0.2059    2.0557    4.3553    0.4925    0.2072    5.3715
-#> 93:    94.5188   -0.2130    2.0646    4.1375    0.4980    0.1996    5.5624
-#> 94:    94.5995   -0.2056    2.0593    3.9306    0.4995    0.2167    5.3581
-#> 95:    94.7276   -0.1868    2.0922    3.7341    0.4863    0.2059    5.3610
-#> 96:    94.5986   -0.1900    2.0771    3.5474    0.4998    0.1956    5.2070
-#> 97:    94.2586   -0.1881    2.1051    3.9558    0.4757    0.1858    5.1561
-#> 98:    94.0716   -0.2098    2.0698    5.6441    0.4539    0.2044    5.1802
-#> 99:    94.2657   -0.2065    2.0679    5.6964    0.4679    0.2190    5.3608
-#> 100:    94.2331   -0.2203    2.0679    5.4116    0.4445    0.2256    5.4031
-#> 101:    93.8634   -0.2222    2.0720    5.1410    0.4279    0.2341    5.3774
-#> 102:    93.7675   -0.2496    2.0232    4.8839    0.4103    0.2224    5.1238
-#> 103:    93.9534   -0.2416    2.0249    4.6397    0.4144    0.2113    5.0031
-#> 104:    94.0631   -0.2442    2.0216    4.8203    0.4119    0.2007    5.1163
-#> 105:    94.0324   -0.2464    2.0092    4.5793    0.4135    0.2047    5.1666
-#> 106:    93.9954   -0.2482    2.0256    4.9167    0.4083    0.2052    5.2515
-#> 107:    94.2189   -0.2507    2.0121    4.6709    0.4072    0.2087    5.3430
-#> 108:    94.3707   -0.2448    2.0215    4.4373    0.4119    0.1996    5.1549
-#> 109:    94.1518   -0.2428    2.0197    4.2155    0.4155    0.1958    5.5480
-#> 110:    93.9287   -0.2571    2.0275    4.0047    0.4152    0.1931    5.8482
-#> 111:    93.9743   -0.2488    2.0202    3.8045    0.4171    0.2084    5.9798
-#> 112:    93.6245   -0.2350    2.0346    3.6142    0.4397    0.1980    6.0270
-#> 113:    94.5370   -0.2330    2.0593    3.9090    0.4422    0.1881    5.4431
-#> 114:    94.5052   -0.2289    2.0555    3.7135    0.4391    0.1787    5.5970
-#> 115:    94.5963   -0.2216    2.0579    3.5279    0.4446    0.1727    5.3901
-#> 116:    94.5059   -0.2293    2.0459    3.3515    0.4407    0.1705    5.2788
-#> 117:    94.6315   -0.2211    2.0564    3.1839    0.4279    0.1689    5.3258
-#> 118:    94.4868   -0.2194    2.0508    4.6523    0.4275    0.1604    5.1421
-#> 119:    94.1809   -0.2232    2.0444    7.0101    0.4302    0.1612    5.3468
-#> 120:    94.0950   -0.2231    2.0482    7.2110    0.4304    0.1625    5.1691
-#> 121:    94.1525   -0.2059    2.0682    6.8504    0.4474    0.1875    5.2811
-#> 122:    94.7122   -0.2154    2.0692    6.6747    0.4366    0.1906    5.3851
-#> 123:    94.2915   -0.2311    2.0431    6.9655    0.4351    0.2021    5.2103
-#> 124:    93.9984   -0.2310    2.0401    6.6173    0.4396    0.2091    5.0920
-#> 125:    94.3668   -0.2068    2.0505    6.2864    0.4983    0.1987    5.3263
-#> 126:    94.3570   -0.2043    2.0525    5.9721    0.5006    0.1887    5.3281
-#> 127:    94.7086   -0.2177    2.0377    5.6735    0.4762    0.1958    5.4003
-#> 128:    94.3565   -0.2173    2.0432    5.3898    0.4754    0.2055    5.5196
-#> 129:    94.4862   -0.2066    2.0639    5.1203    0.4807    0.1952    5.4783
-#> 130:    94.6107   -0.2026    2.0908    4.8643    0.4579    0.1855    5.6186
-#> 131:    94.6831   -0.1907    2.0920    4.6211    0.4710    0.1762    5.4859
-#> 132:    94.7035   -0.2052    2.0733    4.6333    0.4492    0.1723    5.2721
-#> 133:    94.1511   -0.2192    2.0615    5.7533    0.4362    0.1905    5.5019
-#> 134:    94.2758   -0.2101    2.0624    5.4656    0.4356    0.1810    5.3233
-#> 135:    94.6546   -0.1960    2.0826    5.1923    0.4281    0.1980    5.2515
-#> 136:    94.0322   -0.2100    2.0770    4.9327    0.4156    0.2103    5.3514
-#> 137:    94.0915   -0.2096    2.0859    5.6044    0.4159    0.2008    5.2755
-#> 138:    94.2452   -0.1983    2.1055    6.0837    0.4213    0.2185    5.0580
-#> 139:    94.5460   -0.1876    2.1093    6.8410    0.4301    0.2288    5.0840
-#> 140:    94.6905   -0.1863    2.1167    7.4689    0.4313    0.2173    5.0868
-#> 141:    94.6425   -0.1703    2.1240    7.0955    0.4522    0.2065    4.9715
-#> 142:    94.2538   -0.1632    2.1514    6.7407    0.4499    0.2059    5.0853
-#> 143:    94.3098   -0.1625    2.1567    6.4037    0.4499    0.2115    5.5860
-#> 144:    94.2802   -0.1716    2.1510    6.0835    0.4535    0.2081    5.1989
-#> 145:    94.1169   -0.1707    2.1523    5.7793    0.4531    0.2109    5.1407
-#> 146:    94.2558   -0.1579    2.1623    5.4903    0.4654    0.2427    5.2652
-#> 147:    93.9440   -0.1587    2.1673    5.2158    0.4611    0.2537    5.2699
-#> 148:    94.4271   -0.1587    2.1586    4.9550    0.4611    0.2595    5.1280
-#> 149:    94.2734   -0.1768    2.1160    4.7073    0.4809    0.2802    4.9251
-#> 150:    94.2406   -0.1928    2.0941    5.4176    0.4626    0.2662    5.0837
-#> 151:    94.4217   -0.1884    2.0965    5.1467    0.4677    0.2538    5.1728
-#> 152:    94.4856   -0.1826    2.1127    5.6736    0.4646    0.2373    5.1522
-#> 153:    94.3458   -0.1686    2.1381    6.3603    0.4760    0.2028    5.2197
-#> 154:    94.3945   -0.1633    2.1370    5.1586    0.4402    0.1955    5.3770
-#> 155:    94.6367   -0.1520    2.1596    6.4738    0.4533    0.1882    5.3345
-#> 156:    94.9050   -0.1521    2.1417    6.8382    0.4532    0.1729    5.2770
-#> 157:    94.5823   -0.1540    2.1326    5.5745    0.4487    0.1813    5.2760
-#> 158:    94.8355   -0.1691    2.1357    5.2979    0.4296    0.1990    5.3177
-#> 159:    94.7330   -0.1740    2.1148    4.0960    0.4476    0.1820    5.3001
-#> 160:    94.4926   -0.1731    2.1123    4.3550    0.4666    0.1817    5.1849
-#> 161:    94.4953   -0.1758    2.1063    4.0311    0.4698    0.1929    5.1371
-#> 162:    94.5639   -0.1753    2.1064    4.3044    0.4692    0.1911    5.1437
-#> 163:    94.5477   -0.1798    2.1041    4.1393    0.4804    0.2002    5.3561
-#> 164:    94.3812   -0.1934    2.1019    3.5760    0.4689    0.1908    5.3231
-#> 165:    94.0978   -0.1924    2.0973    2.2052    0.4743    0.1962    5.2813
-#> 166:    94.1374   -0.2043    2.0834    2.5477    0.4639    0.1904    5.3277
-#> 167:    94.1587   -0.2036    2.0797    2.7035    0.4561    0.1951    5.3106
-#> 168:    94.1518   -0.2166    2.0654    2.4969    0.4405    0.2090    5.3148
-#> 169:    94.3328   -0.2164    2.0652    2.3067    0.4455    0.1993    5.2385
-#> 170:    94.6029   -0.2176    2.0456    1.7913    0.4478    0.2085    5.4589
-#> 171:    94.2690   -0.2189    2.0635    1.8133    0.4496    0.1999    5.4918
-#> 172:    94.3227   -0.2120    2.0643    1.7763    0.4337    0.2063    5.4992
-#> 173:    94.3099   -0.2039    2.0892    1.1103    0.4350    0.2201    5.5148
-#> 174:    94.3192   -0.1895    2.1140    0.9817    0.4454    0.2078    5.5249
-#> 175:    94.2327   -0.1967    2.0939    0.9890    0.4361    0.1876    5.6321
-#> 176:    94.2707   -0.1989    2.0958    1.3001    0.4405    0.1790    5.6494
-#> 177:    94.0762   -0.2024    2.0908    0.9179    0.4426    0.1778    5.7085
-#> 178:    94.1807   -0.2074    2.0761    1.2663    0.4237    0.2064    5.5157
-#> 179:    94.2221   -0.2029    2.1083    2.0148    0.4270    0.2023    5.6770
-#> 180:    94.5889   -0.1975    2.0974    1.5302    0.4223    0.1778    5.7495
-#> 181:    94.4280   -0.2163    2.0648    1.8829    0.3908    0.1994    5.3948
-#> 182:    94.7076   -0.2247    2.0340    2.1148    0.4238    0.2062    5.4167
-#> 183:    94.5127   -0.2292    2.0317    3.0950    0.4302    0.2160    5.5009
-#> 184:    94.2522   -0.2335    2.0515    2.8900    0.4265    0.2038    5.2995
-#> 185:    94.2331   -0.2330    2.0431    3.3282    0.4276    0.2044    5.2220
-#> 186:    94.2207   -0.2259    2.0512    4.0568    0.4253    0.2008    5.2307
-#> 187:    94.5124   -0.2188    2.0603    3.0941    0.4381    0.1962    5.6927
-#> 188:    94.7691   -0.2454    2.0193    3.1090    0.4409    0.2012    5.5051
-#> 189:    94.5693   -0.2399    2.0169    3.1069    0.4292    0.1883    5.4354
-#> 190:    94.5742   -0.2318    2.0256    4.4216    0.4200    0.1932    5.3851
-#> 191:    94.3882   -0.2475    1.9949    4.5490    0.4366    0.1972    5.2470
-#> 192:    94.4267   -0.2478    1.9943    4.3327    0.4281    0.1995    5.2792
-#> 193:    94.6313   -0.2522    1.9703    3.5911    0.4321    0.1944    5.6218
-#> 194:    94.4345   -0.2616    1.9704    3.2209    0.4260    0.1925    5.5199
-#> 195:    94.6135   -0.2614    1.9622    2.1481    0.4264    0.1879    5.5750
-#> 196:    94.7574   -0.2324    2.0049    1.3351    0.4661    0.1738    5.6590
-#> 197:    94.8293   -0.2064    2.0452    1.6807    0.4904    0.1600    5.7639
-#> 198:    94.6372   -0.2157    2.0307    1.6350    0.5008    0.1524    5.6539
-#> 199:    94.5600   -0.2145    2.0318    1.5133    0.4982    0.1604    5.7178
-#> 200:    94.6945   -0.2100    2.0475    1.4526    0.5066    0.1649    5.6094
-#> 201:    94.5335   -0.2025    2.0594    1.3754    0.5066    0.1681    5.6560
-#> 202:    94.4663   -0.1992    2.0657    1.3622    0.5074    0.1665    5.6522
-#> 203:    94.4750   -0.1956    2.0762    1.3218    0.5051    0.1648    5.5985
-#> 204:    94.4206   -0.1916    2.0795    1.3219    0.5066    0.1593    5.5864
-#> 205:    94.4408   -0.1891    2.0816    1.2934    0.5089    0.1553    5.5967
-#> 206:    94.4631   -0.1863    2.0859    1.2768    0.5108    0.1522    5.6212
-#> 207:    94.4742   -0.1825    2.0912    1.3219    0.5122    0.1479    5.6704
-#> 208:    94.4802   -0.1789    2.0950    1.3488    0.5137    0.1450    5.7072
-#> 209:    94.4734   -0.1756    2.1019    1.3165    0.5155    0.1423    5.7458
-#> 210:    94.4589   -0.1742    2.1056    1.3379    0.5156    0.1409    5.7722
-#> 211:    94.4513   -0.1727    2.1083    1.3395    0.5192    0.1395    5.7707
-#> 212:    94.4422   -0.1718    2.1096    1.3506    0.5219    0.1384    5.7602
-#> 213:    94.4503   -0.1704    2.1112    1.3519    0.5233    0.1377    5.7705
-#> 214:    94.4387   -0.1688    2.1143    1.3620    0.5238    0.1374    5.7627
-#> 215:    94.4468   -0.1677    2.1171    1.3815    0.5236    0.1366    5.7552
-#> 216:    94.4314   -0.1671    2.1191    1.4034    0.5217    0.1362    5.7279
-#> 217:    94.4134   -0.1669    2.1206    1.4118    0.5197    0.1363    5.7109
-#> 218:    94.3896   -0.1665    2.1219    1.3959    0.5181    0.1381    5.6979
-#> 219:    94.3836   -0.1667    2.1226    1.3965    0.5160    0.1402    5.6829
-#> 220:    94.3740   -0.1674    2.1219    1.4130    0.5144    0.1419    5.6839
-#> 221:    94.3663   -0.1677    2.1216    1.4134    0.5131    0.1436    5.6717
-#> 222:    94.3498   -0.1683    2.1212    1.4170    0.5117    0.1453    5.6595
-#> 223:    94.3416   -0.1687    2.1219    1.4195    0.5105    0.1467    5.6587
-#> 224:    94.3412   -0.1687    2.1222    1.4245    0.5097    0.1474    5.6517
-#> 225:    94.3323   -0.1685    2.1235    1.4231    0.5093    0.1484    5.6419
-#> 226:    94.3228   -0.1686    2.1239    1.4167    0.5088    0.1493    5.6305
-#> 227:    94.3135   -0.1688    2.1241    1.4162    0.5084    0.1502    5.6197
-#> 228:    94.3088   -0.1686    2.1251    1.4170    0.5088    0.1515    5.6124
-#> 229:    94.2995   -0.1685    2.1257    1.4316    0.5092    0.1527    5.6079
-#> 230:    94.2864   -0.1690    2.1256    1.4492    0.5088    0.1534    5.6042
-#> 231:    94.2783   -0.1688    2.1260    1.4606    0.5085    0.1548    5.6037
-#> 232:    94.2725   -0.1687    2.1267    1.4571    0.5083    0.1557    5.6020
-#> 233:    94.2692   -0.1682    2.1279    1.4649    0.5076    0.1570    5.6027
-#> 234:    94.2697   -0.1678    2.1292    1.4540    0.5070    0.1584    5.5990
-#> 235:    94.2623   -0.1673    2.1302    1.4424    0.5064    0.1593    5.5919
-#> 236:    94.2610   -0.1667    2.1313    1.4255    0.5055    0.1599    5.5953
-#> 237:    94.2660   -0.1663    2.1322    1.4242    0.5053    0.1605    5.5922
-#> 238:    94.2753   -0.1666    2.1320    1.4370    0.5044    0.1611    5.5891
-#> 239:    94.2821   -0.1662    2.1326    1.4395    0.5036    0.1629    5.5864
-#> 240:    94.2886   -0.1661    2.1330    1.4375    0.5028    0.1644    5.5815
-#> 241:    94.2934   -0.1664    2.1329    1.4276    0.5020    0.1661    5.5777
-#> 242:    94.2963   -0.1664    2.1329    1.4247    0.5012    0.1677    5.5704
-#> 243:    94.2931   -0.1666    2.1328    1.4269    0.5008    0.1690    5.5631
-#> 244:    94.2919   -0.1667    2.1326    1.4279    0.5003    0.1701    5.5610
-#> 245:    94.2959   -0.1675    2.1316    1.4289    0.4993    0.1705    5.5524
-#> 246:    94.2992   -0.1683    2.1305    1.4378    0.4986    0.1706    5.5436
-#> 247:    94.2997   -0.1689    2.1296    1.4461    0.4977    0.1707    5.5383
-#> 248:    94.2978   -0.1693    2.1290    1.4430    0.4970    0.1714    5.5362
-#> 249:    94.2991   -0.1697    2.1285    1.4495    0.4963    0.1720    5.5379
-#> 250:    94.3068   -0.1702    2.1279    1.4556    0.4954    0.1723    5.5390
-#> 251:    94.3097   -0.1707    2.1272    1.4588    0.4936    0.1729    5.5342
-#> 252:    94.3104   -0.1711    2.1267    1.4582    0.4919    0.1739    5.5310
-#> 253:    94.3099   -0.1715    2.1262    1.4551    0.4903    0.1746    5.5279
-#> 254:    94.3110   -0.1721    2.1255    1.4592    0.4886    0.1758    5.5223
-#> 255:    94.3111   -0.1731    2.1236    1.4755    0.4878    0.1775    5.5175
-#> 256:    94.3096   -0.1735    2.1227    1.4971    0.4875    0.1784    5.5162
-#> 257:    94.3079   -0.1738    2.1222    1.5277    0.4874    0.1795    5.5132
-#> 258:    94.3103   -0.1741    2.1217    1.5521    0.4872    0.1806    5.5112
-#> 259:    94.3148   -0.1745    2.1212    1.5788    0.4868    0.1817    5.5066
-#> 260:    94.3170   -0.1750    2.1205    1.6038    0.4863    0.1832    5.5007
-#> 261:    94.3158   -0.1756    2.1197    1.6324    0.4857    0.1849    5.4968
-#> 262:    94.3141   -0.1763    2.1186    1.6503    0.4850    0.1866    5.4918
-#> 263:    94.3135   -0.1764    2.1184    1.6658    0.4849    0.1879    5.4910
-#> 264:    94.3121   -0.1767    2.1183    1.6841    0.4848    0.1893    5.4875
-#> 265:    94.3098   -0.1769    2.1184    1.7115    0.4847    0.1903    5.4832
-#> 266:    94.3087   -0.1768    2.1188    1.7162    0.4845    0.1911    5.4783
-#> 267:    94.3082   -0.1767    2.1191    1.7209    0.4842    0.1920    5.4735
-#> 268:    94.3094   -0.1764    2.1198    1.7314    0.4837    0.1926    5.4720
-#> 269:    94.3074   -0.1764    2.1199    1.7340    0.4831    0.1938    5.4718
-#> 270:    94.3025   -0.1764    2.1200    1.7440    0.4832    0.1949    5.4720
-#> 271:    94.3025   -0.1769    2.1194    1.7538    0.4829    0.1958    5.4748
-#> 272:    94.3039   -0.1772    2.1191    1.7664    0.4829    0.1966    5.4773
-#> 273:    94.3046   -0.1773    2.1192    1.7820    0.4826    0.1976    5.4754
-#> 274:    94.3051   -0.1774    2.1193    1.7895    0.4823    0.1988    5.4735
-#> 275:    94.3026   -0.1773    2.1193    1.7891    0.4819    0.1998    5.4749
-#> 276:    94.3034   -0.1771    2.1195    1.7875    0.4812    0.2010    5.4829
-#> 277:    94.3047   -0.1771    2.1197    1.7843    0.4805    0.2026    5.4878
-#> 278:    94.3067   -0.1771    2.1197    1.7747    0.4799    0.2039    5.4888
-#> 279:    94.3066   -0.1768    2.1202    1.7772    0.4795    0.2049    5.4889
-#> 280:    94.3035   -0.1768    2.1203    1.7797    0.4788    0.2062    5.4888
-#> 281:    94.2961   -0.1771    2.1203    1.7789    0.4782    0.2068    5.4874
-#> 282:    94.2893   -0.1772    2.1203    1.7797    0.4777    0.2072    5.4865
-#> 283:    94.2880   -0.1776    2.1198    1.7743    0.4772    0.2074    5.4856
-#> 284:    94.2897   -0.1779    2.1195    1.7717    0.4768    0.2076    5.4836
-#> 285:    94.2922   -0.1781    2.1194    1.7756    0.4765    0.2075    5.4818
-#> 286:    94.2964   -0.1783    2.1190    1.7759    0.4763    0.2074    5.4798
-#> 287:    94.2991   -0.1787    2.1181    1.7884    0.4761    0.2075    5.4769
-#> 288:    94.2980   -0.1793    2.1171    1.7901    0.4756    0.2077    5.4772
-#> 289:    94.2948   -0.1797    2.1166    1.7957    0.4752    0.2077    5.4763
-#> 290:    94.2922   -0.1801    2.1161    1.8012    0.4749    0.2074    5.4752
-#> 291:    94.2891   -0.1803    2.1157    1.8016    0.4747    0.2073    5.4743
-#> 292:    94.2890   -0.1805    2.1155    1.8012    0.4746    0.2072    5.4743
-#> 293:    94.2874   -0.1808    2.1152    1.8012    0.4743    0.2073    5.4743
-#> 294:    94.2841   -0.1811    2.1148    1.8003    0.4740    0.2075    5.4758
-#> 295:    94.2834   -0.1813    2.1143    1.7982    0.4743    0.2075    5.4766
-#> 296:    94.2817   -0.1816    2.1138    1.7997    0.4745    0.2074    5.4756
-#> 297:    94.2772   -0.1820    2.1131    1.8025    0.4747    0.2074    5.4778
-#> 298:    94.2759   -0.1822    2.1125    1.8097    0.4747    0.2073    5.4781
-#> 299:    94.2752   -0.1825    2.1120    1.8176    0.4748    0.2071    5.4784
-#> 300:    94.2758   -0.1828    2.1115    1.8353    0.4750    0.2069    5.4771
-#> 301:    94.2789   -0.1829    2.1113    1.8511    0.4749    0.2066    5.4767
-#> 302:    94.2808   -0.1833    2.1107    1.8541    0.4747    0.2065    5.4785
-#> 303:    94.2832   -0.1836    2.1103    1.8571    0.4745    0.2064    5.4789
-#> 304:    94.2838   -0.1840    2.1097    1.8584    0.4743    0.2064    5.4792
-#> 305:    94.2835   -0.1843    2.1090    1.8633    0.4741    0.2066    5.4790
-#> 306:    94.2868   -0.1847    2.1083    1.8633    0.4738    0.2069    5.4802
-#> 307:    94.2909   -0.1851    2.1076    1.8702    0.4737    0.2072    5.4787
-#> 308:    94.2916   -0.1857    2.1067    1.8754    0.4735    0.2075    5.4773
-#> 309:    94.2889   -0.1860    2.1062    1.8785    0.4732    0.2078    5.4774
-#> 310:    94.2875   -0.1863    2.1059    1.8854    0.4727    0.2082    5.4763
-#> 311:    94.2889   -0.1867    2.1053    1.8873    0.4722    0.2087    5.4746
-#> 312:    94.2889   -0.1870    2.1047    1.8956    0.4717    0.2090    5.4748
-#> 313:    94.2836   -0.1873    2.1044    1.8980    0.4711    0.2093    5.4721
-#> 314:    94.2801   -0.1876    2.1041    1.8924    0.4706    0.2096    5.4718
-#> 315:    94.2768   -0.1880    2.1038    1.8875    0.4701    0.2096    5.4727
-#> 316:    94.2766   -0.1883    2.1035    1.8854    0.4697    0.2097    5.4730
-#> 317:    94.2779   -0.1886    2.1030    1.8808    0.4693    0.2099    5.4725
-#> 318:    94.2806   -0.1889    2.1024    1.8789    0.4688    0.2101    5.4713
-#> 319:    94.2853   -0.1891    2.1018    1.8852    0.4684    0.2104    5.4690
-#> 320:    94.2867   -0.1894    2.1016    1.8898    0.4680    0.2106    5.4677
-#> 321:    94.2883   -0.1897    2.1013    1.8975    0.4676    0.2108    5.4656
-#> 322:    94.2864   -0.1899    2.1011    1.9078    0.4672    0.2109    5.4622
-#> 323:    94.2831   -0.1902    2.1009    1.9181    0.4668    0.2109    5.4593
-#> 324:    94.2799   -0.1904    2.1008    1.9355    0.4665    0.2109    5.4599
-#> 325:    94.2802   -0.1905    2.1007    1.9474    0.4660    0.2112    5.4608
-#> 326:    94.2808   -0.1907    2.1006    1.9656    0.4654    0.2114    5.4606
-#> 327:    94.2815   -0.1907    2.1006    1.9851    0.4649    0.2118    5.4596
-#> 328:    94.2805   -0.1908    2.1007    2.0051    0.4644    0.2120    5.4584
-#> 329:    94.2810   -0.1909    2.1004    2.0162    0.4638    0.2124    5.4566
-#> 330:    94.2812   -0.1912    2.0999    2.0210    0.4632    0.2131    5.4548
-#> 331:    94.2830   -0.1915    2.0994    2.0253    0.4625    0.2136    5.4520
-#> 332:    94.2835   -0.1920    2.0987    2.0288    0.4619    0.2142    5.4493
-#> 333:    94.2832   -0.1924    2.0981    2.0365    0.4615    0.2148    5.4463
-#> 334:    94.2845   -0.1928    2.0976    2.0433    0.4611    0.2153    5.4436
-#> 335:    94.2856   -0.1931    2.0971    2.0423    0.4607    0.2158    5.4405
-#> 336:    94.2886   -0.1936    2.0963    2.0400    0.4606    0.2165    5.4386
-#> 337:    94.2888   -0.1939    2.0957    2.0352    0.4604    0.2171    5.4376
-#> 338:    94.2879   -0.1944    2.0950    2.0360    0.4600    0.2179    5.4361
-#> 339:    94.2860   -0.1947    2.0946    2.0418    0.4599    0.2186    5.4342
-#> 340:    94.2842   -0.1951    2.0940    2.0455    0.4597    0.2192    5.4324
-#> 341:    94.2804   -0.1954    2.0934    2.0535    0.4596    0.2199    5.4310
-#> 342:    94.2772   -0.1958    2.0928    2.0586    0.4594    0.2204    5.4310
-#> 343:    94.2753   -0.1962    2.0921    2.0604    0.4592    0.2209    5.4304
-#> 344:    94.2749   -0.1965    2.0916    2.0591    0.4589    0.2214    5.4305
-#> 345:    94.2757   -0.1969    2.0911    2.0582    0.4586    0.2220    5.4302
-#> 346:    94.2774   -0.1972    2.0906    2.0554    0.4584    0.2225    5.4301
-#> 347:    94.2772   -0.1974    2.0901    2.0533    0.4583    0.2230    5.4298
-#> 348:    94.2769   -0.1977    2.0895    2.0497    0.4581    0.2235    5.4302
-#> 349:    94.2792   -0.1980    2.0890    2.0439    0.4579    0.2241    5.4327
-#> 350:    94.2825   -0.1983    2.0884    2.0391    0.4577    0.2245    5.4358
-#> 351:    94.2849   -0.1985    2.0879    2.0352    0.4576    0.2251    5.4399
-#> 352:    94.2871   -0.1988    2.0874    2.0396    0.4576    0.2257    5.4414
-#> 353:    94.2888   -0.1991    2.0869    2.0407    0.4573    0.2262    5.4417
-#> 354:    94.2914   -0.1994    2.0863    2.0383    0.4571    0.2268    5.4417
-#> 355:    94.2933   -0.1996    2.0859    2.0385    0.4570    0.2275    5.4418
-#> 356:    94.2932   -0.1999    2.0853    2.0377    0.4569    0.2284    5.4426
-#> 357:    94.2944   -0.2001    2.0850    2.0362    0.4566    0.2292    5.4423
-#> 358:    94.2948   -0.2003    2.0847    2.0415    0.4562    0.2299    5.4409
-#> 359:    94.2950   -0.2005    2.0843    2.0452    0.4558    0.2304    5.4393
-#> 360:    94.2967   -0.2008    2.0840    2.0514    0.4554    0.2307    5.4385
-#> 361:    94.2983   -0.2009    2.0839    2.0676    0.4551    0.2308    5.4386
-#> 362:    94.2992   -0.2009    2.0840    2.0770    0.4549    0.2307    5.4370
-#> 363:    94.2991   -0.2008    2.0841    2.0831    0.4550    0.2306    5.4348
-#> 364:    94.2982   -0.2007    2.0843    2.0892    0.4549    0.2304    5.4348
-#> 365:    94.2951   -0.2005    2.0847    2.1002    0.4551    0.2302    5.4347
-#> 366:    94.2938   -0.2004    2.0850    2.1176    0.4553    0.2300    5.4343
-#> 367:    94.2945   -0.2003    2.0850    2.1310    0.4553    0.2298    5.4346
-#> 368:    94.2956   -0.2003    2.0851    2.1436    0.4554    0.2295    5.4323
-#> 369:    94.2960   -0.2003    2.0850    2.1526    0.4555    0.2293    5.4309
-#> 370:    94.2964   -0.2003    2.0848    2.1577    0.4555    0.2292    5.4295
-#> 371:    94.2965   -0.2004    2.0847    2.1621    0.4555    0.2290    5.4278
-#> 372:    94.2972   -0.2004    2.0847    2.1635    0.4556    0.2285    5.4275
-#> 373:    94.2975   -0.2003    2.0848    2.1643    0.4556    0.2282    5.4275
-#> 374:    94.2985   -0.2004    2.0847    2.1648    0.4556    0.2277    5.4270
-#> 375:    94.3001   -0.2004    2.0846    2.1682    0.4555    0.2273    5.4255
-#> 376:    94.3024   -0.2005    2.0845    2.1692    0.4555    0.2268    5.4246
-#> 377:    94.3050   -0.2005    2.0843    2.1700    0.4555    0.2264    5.4239
-#> 378:    94.3041   -0.2005    2.0843    2.1680    0.4555    0.2258    5.4242
-#> 379:    94.3034   -0.2006    2.0842    2.1688    0.4554    0.2255    5.4233
-#> 380:    94.3027   -0.2007    2.0840    2.1754    0.4554    0.2250    5.4222
-#> 381:    94.3015   -0.2008    2.0839    2.1806    0.4553    0.2246    5.4205
-#> 382:    94.3006   -0.2009    2.0837    2.1812    0.4552    0.2242    5.4194
-#> 383:    94.3004   -0.2010    2.0835    2.1835    0.4551    0.2236    5.4178
-#> 384:    94.3001   -0.2011    2.0834    2.1895    0.4550    0.2232    5.4159
-#> 385:    94.3005   -0.2012    2.0834    2.1910    0.4547    0.2228    5.4148
-#> 386:    94.2993   -0.2013    2.0834    2.1926    0.4545    0.2224    5.4139
-#> 387:    94.2974   -0.2014    2.0834    2.1956    0.4543    0.2221    5.4135
-#> 388:    94.2964   -0.2014    2.0835    2.1979    0.4541    0.2218    5.4124
-#> 389:    94.2956   -0.2013    2.0837    2.1974    0.4540    0.2215    5.4117
-#> 390:    94.2962   -0.2013    2.0838    2.1995    0.4538    0.2213    5.4115
-#> 391:    94.2962   -0.2013    2.0838    2.1987    0.4537    0.2211    5.4116
-#> 392:    94.2956   -0.2013    2.0839    2.2007    0.4536    0.2209    5.4111
-#> 393:    94.2954   -0.2012    2.0839    2.2041    0.4535    0.2207    5.4106
-#> 394:    94.2953   -0.2012    2.0840    2.2033    0.4535    0.2205    5.4103
-#> 395:    94.2964   -0.2012    2.0841    2.2052    0.4533    0.2203    5.4098
-#> 396:    94.2950   -0.2012    2.0841    2.2123    0.4532    0.2202    5.4081
-#> 397:    94.2940   -0.2011    2.0843    2.2227    0.4533    0.2201    5.4070
-#> 398:    94.2938   -0.2011    2.0842    2.2283    0.4534    0.2201    5.4065
-#> 399:    94.2930   -0.2012    2.0842    2.2296    0.4535    0.2201    5.4066
-#> 400:    94.2931   -0.2011    2.0844    2.2345    0.4537    0.2199    5.4071
-#> 401:    94.2926   -0.2009    2.0846    2.2414    0.4539    0.2198    5.4067
-#> 402:    94.2916   -0.2008    2.0848    2.2478    0.4541    0.2196    5.4070
-#> 403:    94.2902   -0.2007    2.0849    2.2543    0.4544    0.2194    5.4071
-#> 404:    94.2895   -0.2007    2.0851    2.2578    0.4546    0.2192    5.4079
-#> 405:    94.2896   -0.2006    2.0853    2.2600    0.4548    0.2190    5.4082
-#> 406:    94.2897   -0.2004    2.0855    2.2636    0.4550    0.2188    5.4086
-#> 407:    94.2880   -0.2002    2.0859    2.2670    0.4554    0.2188    5.4079
-#> 408:    94.2883   -0.1999    2.0861    2.2735    0.4556    0.2189    5.4076
-#> 409:    94.2874   -0.1997    2.0865    2.2822    0.4559    0.2190    5.4073
-#> 410:    94.2861   -0.1995    2.0867    2.2861    0.4563    0.2190    5.4062
-#> 411:    94.2861   -0.1993    2.0869    2.2883    0.4566    0.2190    5.4049
-#> 412:    94.2869   -0.1991    2.0872    2.2926    0.4570    0.2190    5.4039
-#> 413:    94.2874   -0.1990    2.0873    2.2936    0.4574    0.2190    5.4031
-#> 414:    94.2881   -0.1988    2.0874    2.2972    0.4577    0.2189    5.4019
-#> 415:    94.2895   -0.1987    2.0876    2.2999    0.4580    0.2188    5.4004
-#> 416:    94.2900   -0.1985    2.0878    2.3003    0.4582    0.2186    5.3997
-#> 417:    94.2917   -0.1984    2.0880    2.2986    0.4583    0.2185    5.3993
-#> 418:    94.2937   -0.1982    2.0882    2.2986    0.4584    0.2183    5.3995
-#> 419:    94.2947   -0.1981    2.0885    2.2993    0.4584    0.2182    5.3995
-#> 420:    94.2954   -0.1979    2.0886    2.2993    0.4585    0.2180    5.3996
-#> 421:    94.2963   -0.1978    2.0888    2.3029    0.4587    0.2180    5.3992
-#> 422:    94.2982   -0.1976    2.0890    2.3074    0.4588    0.2178    5.4000
-#> 423:    94.3001   -0.1975    2.0891    2.3099    0.4589    0.2178    5.3999
-#> 424:    94.3007   -0.1974    2.0891    2.3106    0.4589    0.2177    5.4001
-#> 425:    94.3016   -0.1973    2.0893    2.3107    0.4589    0.2176    5.3997
-#> 426:    94.3021   -0.1972    2.0894    2.3119    0.4590    0.2175    5.3990
-#> 427:    94.3009   -0.1972    2.0894    2.3100    0.4590    0.2175    5.3971
-#> 428:    94.2998   -0.1972    2.0895    2.3070    0.4590    0.2175    5.3966
-#> 429:    94.2988   -0.1973    2.0895    2.3033    0.4590    0.2175    5.3958
-#> 430:    94.2968   -0.1973    2.0895    2.3028    0.4590    0.2174    5.3955
-#> 431:    94.2950   -0.1973    2.0895    2.3004    0.4589    0.2174    5.3954
-#> 432:    94.2944   -0.1973    2.0896    2.2966    0.4589    0.2174    5.3956
-#> 433:    94.2950   -0.1972    2.0897    2.2942    0.4589    0.2176    5.3959
-#> 434:    94.2949   -0.1972    2.0898    2.2911    0.4589    0.2177    5.3955
-#> 435:    94.2943   -0.1971    2.0900    2.2914    0.4588    0.2179    5.3943
-#> 436:    94.2943   -0.1970    2.0902    2.2895    0.4586    0.2180    5.3948
-#> 437:    94.2955   -0.1970    2.0903    2.2890    0.4585    0.2181    5.3954
-#> 438:    94.2961   -0.1969    2.0905    2.2918    0.4584    0.2183    5.3958
-#> 439:    94.2954   -0.1968    2.0906    2.2943    0.4583    0.2185    5.3953
-#> 440:    94.2944   -0.1968    2.0906    2.2977    0.4581    0.2187    5.3949
-#> 441:    94.2931   -0.1968    2.0907    2.2991    0.4578    0.2188    5.3952
-#> 442:    94.2926   -0.1968    2.0908    2.2990    0.4575    0.2188    5.3951
-#> 443:    94.2922   -0.1968    2.0909    2.2990    0.4573    0.2188    5.3938
-#> 444:    94.2917   -0.1969    2.0909    2.2995    0.4571    0.2188    5.3927
-#> 445:    94.2901   -0.1969    2.0910    2.3067    0.4568    0.2187    5.3911
-#> 446:    94.2898   -0.1969    2.0910    2.3082    0.4566    0.2187    5.3891
-#> 447:    94.2897   -0.1969    2.0910    2.3121    0.4564    0.2187    5.3871
-#> 448:    94.2883   -0.1970    2.0911    2.3180    0.4562    0.2188    5.3858
-#> 449:    94.2879   -0.1970    2.0912    2.3210    0.4561    0.2188    5.3851
-#> 450:    94.2874   -0.1970    2.0914    2.3243    0.4559    0.2188    5.3841
-#> 451:    94.2873   -0.1969    2.0915    2.3247    0.4557    0.2188    5.3834
-#> 452:    94.2873   -0.1969    2.0917    2.3249    0.4555    0.2187    5.3839
-#> 453:    94.2868   -0.1968    2.0920    2.3257    0.4554    0.2187    5.3831
-#> 454:    94.2857   -0.1967    2.0922    2.3240    0.4552    0.2187    5.3824
-#> 455:    94.2848   -0.1965    2.0925    2.3214    0.4551    0.2186    5.3822
-#> 456:    94.2838   -0.1964    2.0929    2.3204    0.4550    0.2185    5.3822
-#> 457:    94.2831   -0.1962    2.0932    2.3202    0.4549    0.2184    5.3819
-#> 458:    94.2831   -0.1961    2.0935    2.3174    0.4548    0.2183    5.3810
-#> 459:    94.2829   -0.1960    2.0938    2.3183    0.4546    0.2183    5.3807
-#> 460:    94.2818   -0.1958    2.0941    2.3213    0.4545    0.2183    5.3802
-#> 461:    94.2812   -0.1956    2.0945    2.3292    0.4544    0.2182    5.3785
-#> 462:    94.2813   -0.1955    2.0948    2.3328    0.4544    0.2182    5.3778
-#> 463:    94.2816   -0.1953    2.0951    2.3364    0.4543    0.2181    5.3770
-#> 464:    94.2810   -0.1952    2.0954    2.3365    0.4542    0.2180    5.3764
-#> 465:    94.2797   -0.1950    2.0957    2.3341    0.4541    0.2179    5.3756
-#> 466:    94.2777   -0.1949    2.0960    2.3368    0.4541    0.2178    5.3750
-#> 467:    94.2755   -0.1949    2.0962    2.3417    0.4539    0.2178    5.3738
-#> 468:    94.2741   -0.1948    2.0965    2.3426    0.4537    0.2177    5.3731
-#> 469:    94.2735   -0.1947    2.0967    2.3410    0.4535    0.2175    5.3729
-#> 470:    94.2731   -0.1946    2.0970    2.3440    0.4534    0.2173    5.3733
-#> 471:    94.2727   -0.1945    2.0972    2.3505    0.4533    0.2171    5.3724
-#> 472:    94.2734   -0.1944    2.0973    2.3550    0.4533    0.2169    5.3719
-#> 473:    94.2745   -0.1944    2.0974    2.3593    0.4533    0.2167    5.3715
-#> 474:    94.2746   -0.1944    2.0975    2.3622    0.4533    0.2166    5.3708
-#> 475:    94.2753   -0.1943    2.0975    2.3673    0.4533    0.2165    5.3701
-#> 476:    94.2760   -0.1943    2.0976    2.3745    0.4534    0.2166    5.3698
-#> 477:    94.2771   -0.1942    2.0978    2.3812    0.4535    0.2166    5.3695
-#> 478:    94.2767   -0.1941    2.0981    2.3891    0.4535    0.2166    5.3691
-#> 479:    94.2762   -0.1940    2.0984    2.3931    0.4534    0.2166    5.3691
-#> 480:    94.2754   -0.1939    2.0986    2.3958    0.4533    0.2166    5.3685
-#> 481:    94.2743   -0.1938    2.0987    2.3990    0.4532    0.2165    5.3677
-#> 482:    94.2733   -0.1937    2.0988    2.3996    0.4531    0.2164    5.3670
-#> 483:    94.2724   -0.1937    2.0989    2.4031    0.4531    0.2163    5.3659
-#> 484:    94.2726   -0.1937    2.0989    2.4035    0.4530    0.2162    5.3651
-#> 485:    94.2722   -0.1937    2.0989    2.4033    0.4530    0.2162    5.3649
-#> 486:    94.2716   -0.1936    2.0991    2.4046    0.4529    0.2163    5.3645
-#> 487:    94.2710   -0.1936    2.0992    2.4078    0.4527    0.2165    5.3643
-#> 488:    94.2693   -0.1936    2.0992    2.4088    0.4525    0.2167    5.3653
-#> 489:    94.2689   -0.1936    2.0993    2.4116    0.4523    0.2170    5.3645
-#> 490:    94.2686   -0.1936    2.0993    2.4105    0.4520    0.2172    5.3644
-#> 491:    94.2685   -0.1935    2.0994    2.4097    0.4518    0.2174    5.3651
-#> 492:    94.2677   -0.1935    2.0995    2.4103    0.4517    0.2175    5.3657
-#> 493:    94.2670   -0.1935    2.0996    2.4112    0.4515    0.2177    5.3661
-#> 494:    94.2668   -0.1935    2.0996    2.4140    0.4514    0.2178    5.3662
-#> 495:    94.2667   -0.1936    2.0996    2.4157    0.4513    0.2179    5.3660
-#> 496:    94.2670   -0.1936    2.0996    2.4163    0.4511    0.2180    5.3668
-#> 497:    94.2664   -0.1936    2.0996    2.4170    0.4510    0.2181    5.3676
-#> 498:    94.2654   -0.1937    2.0996    2.4128    0.4509    0.2181    5.3683
-#> 499:    94.2643   -0.1937    2.0996    2.4109    0.4508    0.2181    5.3679
-#> 500:    94.2635   -0.1938    2.0995    2.4122    0.4508    0.2181    5.3682
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 | log_alpha |  log_beta |     sigma |
-#> |.....................|        o1 |        o2 |        o3 |...........|
-#> |    1|     296.31831 |     1.000 |    -1.000 |   -0.9520 |   -0.9547 |
-#> |.....................|   -0.9791 |   -0.9725 |   -0.9706 |...........|
-#> |    U|     296.31831 |     94.44 |   -0.2226 |     2.048 |     1.920 |
-#> |.....................|    0.7656 |     1.078 |     1.168 |...........|
-#> |    X|     296.31831 |     94.44 |    0.8004 |     7.754 |     1.920 |
-#> |.....................|    0.7656 |     1.078 |     1.168 |...........|
-#> |    G|    Gill Diff. |     9.126 |  0.009097 |  -0.01177 |    -32.33 |
-#> |.....................|     6.099 |    -8.436 |    -11.35 |...........|
-#> |    2|     594.25462 |    0.7531 |    -1.000 |   -0.9517 |  -0.07988 |
-#> |.....................|    -1.144 |   -0.7442 |   -0.6636 |...........|
-#> |    U|     594.25462 |     71.12 |   -0.2229 |     2.049 |     2.760 |
-#> |.....................|    0.6392 |     1.324 |     1.526 |...........|
-#> |    X|     594.25462 |     71.12 |    0.8002 |     7.756 |     2.760 |
-#> |.....................|    0.6392 |     1.324 |     1.526 |...........|
-#> |    3|     298.71818 |    0.9753 |    -1.000 |   -0.9520 |   -0.8672 |
-#> |.....................|   -0.9956 |   -0.9497 |   -0.9399 |...........|
-#> |    U|     298.71818 |     92.11 |   -0.2226 |     2.048 |     2.004 |
-#> |.....................|    0.7529 |     1.103 |     1.204 |...........|
-#> |    X|     298.71818 |     92.11 |    0.8004 |     7.754 |     2.004 |
-#> |.....................|    0.7529 |     1.103 |     1.204 |...........|
-#> |    4|     295.79061 |    0.9925 |    -1.000 |   -0.9520 |   -0.9282 |
-#> |.....................|   -0.9841 |   -0.9656 |   -0.9613 |...........|
-#> |    U|     295.79061 |     93.73 |   -0.2226 |     2.048 |     1.945 |
-#> |.....................|    0.7617 |     1.086 |     1.179 |...........|
-#> |    X|     295.79061 |     93.73 |    0.8004 |     7.754 |     1.945 |
-#> |.....................|    0.7617 |     1.086 |     1.179 |...........|
-#> |    F| Forward Diff. |    -134.6 |  -0.07715 |   -0.3541 |    -29.37 |
-#> |.....................|     6.863 |    -7.752 |    -10.79 |...........|
-#> |    5|     294.44078 |     1.001 |    -1.000 |   -0.9520 |   -0.9020 |
-#> |.....................|   -0.9892 |   -0.9588 |   -0.9521 |...........|
-#> |    U|     294.44078 |     94.55 |   -0.2226 |     2.048 |     1.970 |
-#> |.....................|    0.7578 |     1.093 |     1.189 |...........|
-#> |    X|     294.44078 |     94.55 |    0.8004 |     7.754 |     1.970 |
-#> |.....................|    0.7578 |     1.093 |     1.189 |...........|
-#> |    F| Forward Diff. |     30.39 |   0.01643 |   0.02646 |    -26.06 |
-#> |.....................|     5.336 |    -7.397 |    -10.44 |...........|
-#> |    6|     293.62741 |    0.9971 |    -1.000 |   -0.9519 |   -0.8750 |
-#> |.....................|   -0.9945 |   -0.9516 |   -0.9423 |...........|
-#> |    U|     293.62741 |     94.17 |   -0.2226 |     2.048 |     1.996 |
-#> |.....................|    0.7538 |     1.101 |     1.201 |...........|
-#> |    X|     293.62741 |     94.17 |    0.8004 |     7.754 |     1.996 |
-#> |.....................|    0.7538 |     1.101 |     1.201 |...........|
-#> |    7|     292.50099 |    0.9961 |    -1.000 |   -0.9519 |   -0.8316 |
-#> |.....................|    -1.003 |   -0.9401 |   -0.9267 |...........|
-#> |    U|     292.50099 |     94.07 |   -0.2226 |     2.048 |     2.038 |
-#> |.....................|    0.7474 |     1.113 |     1.219 |...........|
-#> |    X|     292.50099 |     94.07 |    0.8004 |     7.755 |     2.038 |
-#> |.....................|    0.7474 |     1.113 |     1.219 |...........|
-#> |    8|     290.76125 |    0.9939 |    -1.000 |   -0.9518 |   -0.7361 |
-#> |.....................|    -1.021 |   -0.9149 |   -0.8925 |...........|
-#> |    U|     290.76125 |     93.87 |   -0.2226 |     2.048 |     2.130 |
-#> |.....................|    0.7332 |     1.140 |     1.259 |...........|
-#> |    X|     290.76125 |     93.87 |    0.8004 |     7.756 |     2.130 |
-#> |.....................|    0.7332 |     1.140 |     1.259 |...........|
-#> |    F| Forward Diff. |    -91.20 |  -0.08176 |   -0.4010 |    -10.74 |
-#> |.....................|     3.658 |    -4.872 |    -7.770 |...........|
-#> |    9|     293.40175 |     1.024 |   -0.9990 |   -0.9455 |   -0.7012 |
-#> |.....................|    -1.060 |   -0.8302 |   -0.7398 |...........|
-#> |    U|     293.40175 |     96.67 |   -0.2216 |     2.055 |     2.163 |
-#> |.....................|    0.7035 |     1.231 |     1.437 |...........|
-#> |    X|     293.40175 |     96.67 |    0.8012 |     7.804 |     2.163 |
-#> |.....................|    0.7035 |     1.231 |     1.437 |...........|
-#> |   10|     292.85583 |     1.019 |   -0.9997 |   -0.9499 |   -0.7242 |
-#> |.....................|    -1.033 |   -0.8898 |   -0.8474 |...........|
-#> |    U|     292.85583 |     96.21 |   -0.2223 |     2.050 |     2.141 |
-#> |.....................|    0.7242 |     1.167 |     1.312 |...........|
-#> |    X|     292.85583 |     96.21 |    0.8007 |     7.770 |     2.141 |
-#> |.....................|    0.7242 |     1.167 |     1.312 |...........|
-#> |   11|     291.55187 |     1.011 |    -1.000 |   -0.9517 |   -0.7341 |
-#> |.....................|    -1.022 |   -0.9140 |   -0.8910 |...........|
-#> |    U|     291.55187 |     95.48 |   -0.2226 |     2.048 |     2.132 |
-#> |.....................|    0.7326 |     1.141 |     1.261 |...........|
-#> |    X|     291.55187 |     95.48 |    0.8004 |     7.756 |     2.132 |
-#> |.....................|    0.7326 |     1.141 |     1.261 |...........|
-#> |   12|     290.49268 |    0.9997 |    -1.000 |   -0.9518 |   -0.7354 |
-#> |.....................|    -1.022 |   -0.9146 |   -0.8920 |...........|
-#> |    U|     290.49268 |     94.41 |   -0.2226 |     2.048 |     2.130 |
-#> |.....................|    0.7330 |     1.141 |     1.259 |...........|
-#> |    X|     290.49268 |     94.41 |    0.8004 |     7.756 |     2.130 |
-#> |.....................|    0.7330 |     1.141 |     1.259 |...........|
-#> |    F| Forward Diff. |     2.619 | -0.007793 |  -0.07320 |    -10.57 |
-#> |.....................|     3.077 |    -4.876 |    -7.795 |...........|
-#> |   13|     290.41825 |    0.9986 |    -1.000 |   -0.9517 |   -0.7312 |
-#> |.....................|    -1.023 |   -0.9126 |   -0.8889 |...........|
-#> |    U|     290.41825 |     94.31 |   -0.2226 |     2.048 |     2.134 |
-#> |.....................|    0.7321 |     1.143 |     1.263 |...........|
-#> |    X|     290.41825 |     94.31 |    0.8004 |     7.756 |     2.134 |
-#> |.....................|    0.7321 |     1.143 |     1.263 |...........|
-#> |   14|     290.31205 |    0.9955 |    -1.000 |   -0.9517 |   -0.7186 |
-#> |.....................|    -1.027 |   -0.9068 |   -0.8796 |...........|
-#> |    U|     290.31205 |     94.01 |   -0.2226 |     2.049 |     2.146 |
-#> |.....................|    0.7292 |     1.149 |     1.274 |...........|
-#> |    X|     290.31205 |     94.01 |    0.8004 |     7.757 |     2.146 |
-#> |.....................|    0.7292 |     1.149 |     1.274 |...........|
-#> |    F| Forward Diff. |    -64.45 |  -0.06351 |   -0.3251 |    -9.485 |
-#> |.....................|     2.861 |    -4.414 |    -7.225 |...........|
-#> |   15|     290.00198 |     1.000 |   -0.9999 |   -0.9510 |   -0.7191 |
-#> |.....................|    -1.030 |   -0.8965 |   -0.8595 |...........|
-#> |    U|     290.00198 |     94.46 |   -0.2225 |     2.049 |     2.146 |
-#> |.....................|    0.7268 |     1.160 |     1.297 |...........|
-#> |    X|     290.00198 |     94.46 |    0.8005 |     7.762 |     2.146 |
-#> |.....................|    0.7268 |     1.160 |     1.297 |...........|
-#> |    F| Forward Diff. |     11.27 | -0.003123 |  -0.03408 |    -9.156 |
-#> |.....................|     2.235 |    -3.823 |    -6.423 |...........|
-#> |   16|     289.83558 |    0.9983 |   -0.9998 |   -0.9502 |   -0.7180 |
-#> |.....................|    -1.031 |   -0.8872 |   -0.8384 |...........|
-#> |    U|     289.83558 |     94.28 |   -0.2224 |     2.050 |     2.147 |
-#> |.....................|    0.7259 |     1.170 |     1.322 |...........|
-#> |    X|     289.83558 |     94.28 |    0.8006 |     7.768 |     2.147 |
-#> |.....................|    0.7259 |     1.170 |     1.322 |...........|
-#> |   17|     289.63307 |    0.9979 |   -0.9995 |   -0.9489 |   -0.7184 |
-#> |.....................|    -1.032 |   -0.8720 |   -0.8037 |...........|
-#> |    U|     289.63307 |     94.24 |   -0.2221 |     2.051 |     2.147 |
-#> |.....................|    0.7248 |     1.186 |     1.363 |...........|
-#> |    X|     289.63307 |     94.24 |    0.8008 |     7.778 |     2.147 |
-#> |.....................|    0.7248 |     1.186 |     1.363 |...........|
-#> |   18|     289.44450 |    0.9972 |   -0.9991 |   -0.9468 |   -0.7190 |
-#> |.....................|    -1.035 |   -0.8473 |   -0.7469 |...........|
-#> |    U|      289.4445 |     94.18 |   -0.2217 |     2.053 |     2.146 |
-#> |.....................|    0.7231 |     1.213 |     1.429 |...........|
-#> |    X|      289.4445 |     94.18 |    0.8011 |     7.794 |     2.146 |
-#> |.....................|    0.7231 |     1.213 |     1.429 |...........|
-#> |    F| Forward Diff. |    -36.76 |  -0.05208 |   -0.1861 |    -9.057 |
-#> |.....................|     2.429 |   -0.6853 |    -1.924 |...........|
-#> |   19|     288.93351 |    0.9984 |   -0.9961 |   -0.9370 |   -0.6306 |
-#> |.....................|    -1.080 |   -0.9120 |   -0.7149 |...........|
-#> |    U|     288.93351 |     94.29 |   -0.2187 |     2.063 |     2.231 |
-#> |.....................|    0.6885 |     1.143 |     1.466 |...........|
-#> |    X|     288.93351 |     94.29 |    0.8035 |     7.871 |     2.231 |
-#> |.....................|    0.6885 |     1.143 |     1.466 |...........|
-#> |    F| Forward Diff. |    -14.48 |  -0.02726 |    0.2181 |    -3.062 |
-#> |.....................|   -0.1976 |    -4.306 |   -0.8806 |...........|
-#> |   20|     288.85238 |     1.002 |   -0.9934 |   -0.9444 |   -0.5654 |
-#> |.....................|    -1.062 |   -0.8288 |   -0.7747 |...........|
-#> |    U|     288.85238 |     94.67 |   -0.2160 |     2.056 |     2.293 |
-#> |.....................|    0.7024 |     1.233 |     1.396 |...........|
-#> |    X|     288.85238 |     94.67 |    0.8057 |     7.813 |     2.293 |
-#> |.....................|    0.7024 |     1.233 |     1.396 |...........|
-#> |    F| Forward Diff. |     40.49 |    0.1537 |    0.2940 |    0.6524 |
-#> |.....................|    0.4942 |    0.3489 |    -3.099 |...........|
-#> |   21|     289.09335 |    0.9960 |    -1.025 |    -1.050 |   -0.5645 |
-#> |.....................|    -1.111 |   -0.8117 |   -0.7552 |...........|
-#> |    U|     289.09335 |     94.07 |   -0.2476 |     1.951 |     2.294 |
-#> |.....................|    0.6648 |     1.251 |     1.419 |...........|
-#> |    X|     289.09335 |     94.07 |    0.7806 |     7.034 |     2.294 |
-#> |.....................|    0.6648 |     1.251 |     1.419 |...........|
-#> |   22|     288.97418 |    0.9945 |    -1.003 |   -0.9755 |   -0.5652 |
-#> |.....................|    -1.076 |   -0.8238 |   -0.7685 |...........|
-#> |    U|     288.97418 |     93.92 |   -0.2254 |     2.025 |     2.294 |
-#> |.....................|    0.6912 |     1.238 |     1.404 |...........|
-#> |    X|     288.97418 |     93.92 |    0.7982 |     7.574 |     2.294 |
-#> |.....................|    0.6912 |     1.238 |     1.404 |...........|
-#> |   23|     288.99640 |    0.9941 |   -0.9963 |   -0.9538 |   -0.5655 |
-#> |.....................|    -1.066 |   -0.8273 |   -0.7723 |...........|
-#> |    U|      288.9964 |     93.88 |   -0.2189 |     2.046 |     2.293 |
-#> |.....................|    0.6990 |     1.235 |     1.399 |...........|
-#> |    X|      288.9964 |     93.88 |    0.8034 |     7.740 |     2.293 |
-#> |.....................|    0.6990 |     1.235 |     1.399 |...........|
-#> |   24|     288.82158 |    0.9975 |   -0.9934 |   -0.9445 |   -0.5655 |
-#> |.....................|    -1.062 |   -0.8288 |   -0.7743 |...........|
-#> |    U|     288.82158 |     94.20 |   -0.2160 |     2.056 |     2.293 |
-#> |.....................|    0.7023 |     1.233 |     1.397 |...........|
-#> |    X|     288.82158 |     94.20 |    0.8057 |     7.813 |     2.293 |
-#> |.....................|    0.7023 |     1.233 |     1.397 |...........|
-#> |    F| Forward Diff. |    -27.98 |   0.07663 |  -0.09902 |    0.6250 |
-#> |.....................|    0.3387 |    0.3777 |    -3.049 |...........|
-#> |   25|     288.78525 |    0.9995 |   -0.9943 |   -0.9465 |   -0.5657 |
-#> |.....................|    -1.059 |   -0.8303 |   -0.7716 |...........|
-#> |    U|     288.78525 |     94.39 |   -0.2169 |     2.054 |     2.293 |
-#> |.....................|    0.7042 |     1.231 |     1.400 |...........|
-#> |    X|     288.78525 |     94.39 |    0.8050 |     7.797 |     2.293 |
-#> |.....................|    0.7042 |     1.231 |     1.400 |...........|
-#> |    F| Forward Diff. |   -0.7037 |   0.08814 | -0.009566 |    0.5597 |
-#> |.....................|    0.2999 |    0.2778 |    -2.968 |...........|
-#> |   26|     288.77680 |     1.000 |   -0.9946 |   -0.9467 |   -0.5664 |
-#> |.....................|    -1.059 |   -0.8311 |   -0.7670 |...........|
-#> |    U|      288.7768 |     94.48 |   -0.2172 |     2.053 |     2.292 |
-#> |.....................|    0.7047 |     1.231 |     1.405 |...........|
-#> |    X|      288.7768 |     94.48 |    0.8048 |     7.795 |     2.292 |
-#> |.....................|    0.7047 |     1.231 |     1.405 |...........|
-#> |    F| Forward Diff. |     12.46 |   0.09472 |   0.05753 |    0.4960 |
-#> |.....................|    0.3156 |    0.2411 |    -2.796 |...........|
-#> |   27|     288.76499 |    0.9995 |   -0.9954 |   -0.9482 |   -0.5665 |
-#> |.....................|    -1.055 |   -0.8326 |   -0.7642 |...........|
-#> |    U|     288.76499 |     94.39 |   -0.2180 |     2.052 |     2.292 |
-#> |.....................|    0.7071 |     1.229 |     1.409 |...........|
-#> |    X|     288.76499 |     94.39 |    0.8042 |     7.783 |     2.292 |
-#> |.....................|    0.7071 |     1.229 |     1.409 |...........|
-#> |    F| Forward Diff. |   -0.8358 |   0.06465 |  -0.06858 |    0.5747 |
-#> |.....................|    0.6430 |    0.1630 |    -2.683 |...........|
-#> |   28|     288.75697 |     1.000 |   -0.9957 |   -0.9484 |   -0.5681 |
-#> |.....................|    -1.059 |   -0.8325 |   -0.7609 |...........|
-#> |    U|     288.75697 |     94.45 |   -0.2183 |     2.052 |     2.291 |
-#> |.....................|    0.7046 |     1.229 |     1.413 |...........|
-#> |    X|     288.75697 |     94.45 |    0.8039 |     7.782 |     2.291 |
-#> |.....................|    0.7046 |     1.229 |     1.413 |...........|
-#> |    F| Forward Diff. |     8.673 |   0.06496 |  -0.02049 |    0.4885 |
-#> |.....................|    0.5066 |    0.1747 |    -2.560 |...........|
-#> |   29|     288.75050 |    0.9994 |   -0.9958 |   -0.9480 |   -0.5696 |
-#> |.....................|    -1.063 |   -0.8317 |   -0.7600 |...........|
-#> |    U|      288.7505 |     94.38 |   -0.2184 |     2.052 |     2.289 |
-#> |.....................|    0.7012 |     1.230 |     1.414 |...........|
-#> |    X|      288.7505 |     94.38 |    0.8038 |     7.785 |     2.289 |
-#> |.....................|    0.7012 |     1.230 |     1.414 |...........|
-#> |    F| Forward Diff. |    -2.463 |   0.04955 |  -0.07455 |    0.3979 |
-#> |.....................|    0.1788 |    0.2263 |    -2.511 |...........|
-#> |   30|     288.74110 |    0.9997 |   -0.9954 |   -0.9459 |   -0.5705 |
-#> |.....................|    -1.061 |   -0.8331 |   -0.7562 |...........|
-#> |    U|      288.7411 |     94.41 |   -0.2180 |     2.054 |     2.289 |
-#> |.....................|    0.7025 |     1.228 |     1.418 |...........|
-#> |    X|      288.7411 |     94.41 |    0.8041 |     7.801 |     2.289 |
-#> |.....................|    0.7025 |     1.228 |     1.418 |...........|
-#> |   31|     288.72064 |    0.9993 |   -0.9939 |   -0.9392 |   -0.5730 |
-#> |.....................|    -1.056 |   -0.8374 |   -0.7455 |...........|
-#> |    U|     288.72064 |     94.37 |   -0.2166 |     2.061 |     2.286 |
-#> |.....................|    0.7068 |     1.224 |     1.431 |...........|
-#> |    X|     288.72064 |     94.37 |    0.8053 |     7.854 |     2.286 |
-#> |.....................|    0.7068 |     1.224 |     1.431 |...........|
-#> |   32|     288.70690 |    0.9989 |   -0.9915 |   -0.9277 |   -0.5774 |
-#> |.....................|    -1.046 |   -0.8449 |   -0.7267 |...........|
-#> |    U|      288.7069 |     94.33 |   -0.2141 |     2.072 |     2.282 |
-#> |.....................|    0.7141 |     1.216 |     1.453 |...........|
-#> |    X|      288.7069 |     94.33 |    0.8073 |     7.944 |     2.282 |
-#> |.....................|    0.7141 |     1.216 |     1.453 |...........|
-#> |    F| Forward Diff. |    -8.246 |   0.08782 |    0.6230 |   -0.2261 |
-#> |.....................|    0.9054 |   -0.5290 |    -1.268 |...........|
-#> |   33|     288.68146 |     1.000 |   -0.9932 |   -0.9567 |   -0.5899 |
-#> |.....................|    -1.067 |   -0.8479 |   -0.7019 |...........|
-#> |    U|     288.68146 |     94.46 |   -0.2158 |     2.043 |     2.270 |
-#> |.....................|    0.6982 |     1.212 |     1.481 |...........|
-#> |    X|     288.68146 |     94.46 |    0.8059 |     7.717 |     2.270 |
-#> |.....................|    0.6982 |     1.212 |     1.481 |...........|
-#> |    F| Forward Diff. |     8.603 |    0.1068 |   -0.4021 |   -0.6499 |
-#> |.....................|    0.1745 |   -0.5873 |   -0.4459 |...........|
-#> |   34|     288.70236 |     1.001 |    -1.018 |   -0.9264 |   -0.5930 |
-#> |.....................|    -1.088 |   -0.8392 |   -0.6985 |...........|
-#> |    U|     288.70236 |     94.50 |   -0.2403 |     2.074 |     2.267 |
-#> |.....................|    0.6822 |     1.222 |     1.485 |...........|
-#> |    X|     288.70236 |     94.50 |    0.7864 |     7.955 |     2.267 |
-#> |.....................|    0.6822 |     1.222 |     1.485 |...........|
-#> |   35|     288.67546 |    0.9997 |   -0.9992 |   -0.9493 |   -0.5906 |
-#> |.....................|    -1.072 |   -0.8457 |   -0.7010 |...........|
-#> |    U|     288.67546 |     94.41 |   -0.2218 |     2.051 |     2.269 |
-#> |.....................|    0.6943 |     1.215 |     1.482 |...........|
-#> |    X|     288.67546 |     94.41 |    0.8011 |     7.775 |     2.269 |
-#> |.....................|    0.6943 |     1.215 |     1.482 |...........|
-#> |    F| Forward Diff. |     1.309 |  -0.03968 |   -0.1448 |   -0.6596 |
-#> |.....................|   0.05856 |   -0.4617 |   -0.3123 |...........|
-#> |   36|     288.67323 |    0.9995 |   -0.9891 |   -0.9462 |   -0.5890 |
-#> |.....................|    -1.074 |   -0.8436 |   -0.6999 |...........|
-#> |    U|     288.67323 |     94.40 |   -0.2117 |     2.054 |     2.271 |
-#> |.....................|    0.6929 |     1.217 |     1.484 |...........|
-#> |    X|     288.67323 |     94.40 |    0.8092 |     7.800 |     2.271 |
-#> |.....................|    0.6929 |     1.217 |     1.484 |...........|
-#> |    F| Forward Diff. |   -0.3529 |    0.1695 |  -0.04594 |   -0.6688 |
-#> |.....................|   -0.2932 |   -0.3576 |   -0.2566 |...........|
-#> |   37|     288.67323 |    0.9995 |   -0.9891 |   -0.9462 |   -0.5890 |
-#> |.....................|    -1.074 |   -0.8436 |   -0.6999 |...........|
-#> |    U|     288.67323 |     94.40 |   -0.2117 |     2.054 |     2.271 |
-#> |.....................|    0.6929 |     1.217 |     1.484 |...........|
-#> |    X|     288.67323 |     94.40 |    0.8092 |     7.800 |     2.271 |
-#> |.....................|    0.6929 |     1.217 |     1.484 |...........|
-#> calculating covariance matrix
+f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem",
+  control = saemControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei",
+  control = foceiControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> calculating covariance matrix
 #> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo

-f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> 1:    93.2375   -1.6690   -4.0126    0.0336    3.3441    0.9789    2.1220    0.5342   18.1447
-#> 2:    92.9778   -1.6369   -3.9297    0.0067    3.1769    1.2515    2.0460    0.5166   11.1022
-#> 3:    92.9382   -1.6747   -3.9496   -0.0050    3.0181    1.1889    1.9437    0.4908    9.5980
-#> 4:    93.4481   -1.8083   -3.9734   -0.0250    2.8672    1.1295    1.8797    0.4662    8.6240
-#> 5:    93.4584   -1.8288   -4.0221    0.0414    2.7238    1.0730    1.8467    0.5161    8.1404
-#> 6:    93.7533   -1.8675   -4.0215    0.0158    2.5876    1.0194    1.8017    0.4911    7.5848
-#> 7:    93.6006   -1.8542   -4.0241   -0.0026    2.4582    0.9684    1.7860    0.4916    7.0796
-#> 8:    93.6918   -1.8416   -3.9940    0.0121    2.3353    0.9200    1.7061    0.4681    6.9985
-#> 9:    93.4789   -1.8738   -3.9845    0.0318    3.1307    0.8740    1.7845    0.4553    6.8335
-#> 10:    93.6048   -1.8723   -4.0154    0.0112    3.1962    0.8303    1.7434    0.4325    7.0681
-#> 11:    93.5135   -1.8675   -3.9905    0.0295    3.2177    0.7888    1.6910    0.4619    6.9572
-#> 12:    93.4407   -1.8790   -3.9877    0.0509    3.4194    0.7493    1.6324    0.5060    6.5755
-#> 13:    93.5033   -1.9250   -4.0416    0.0734    3.2485    0.7295    1.7369    0.4807    6.3881
-#> 14:    93.4276   -1.9082   -4.0516    0.0558    3.0860    0.7281    1.7241    0.4567    5.9840
-#> 15:    93.3041   -1.9256   -4.0718    0.0854    3.4389    0.7293    1.7446    0.4524    5.8195
-#> 16:    93.2979   -1.9297   -4.0624    0.0730    3.2670    0.7239    1.7476    0.4298    5.7629
-#> 17:    93.3522   -1.9570   -4.0876    0.1304    3.3053    0.7020    1.7402    0.4083    5.6926
-#> 18:    93.3500   -1.9652   -4.0816    0.1350    3.1400    0.7130    1.7217    0.3879    5.5714
-#> 19:    93.3822   -1.9519   -4.0961    0.1322    2.9830    0.7087    1.7228    0.3745    5.4176
-#> 20:    93.2823   -1.9490   -4.0841    0.1238    2.8339    0.6988    1.7659    0.3753    5.5279
-#> 21:    93.5951   -1.9298   -4.0874    0.1345    2.6922    0.6665    1.7724    0.3645    5.4414
-#> 22:    93.5052   -1.9469   -4.0739    0.1260    3.1244    0.6776    1.7629    0.3618    5.5395
-#> 23:    93.4734   -1.9952   -4.0909    0.1472    3.0340    0.7225    1.8104    0.3437    5.5072
-#> 24:    93.8816   -1.9639   -4.0914    0.1511    2.8824    0.7215    1.8586    0.3324    5.6009
-#> 25:    93.5874   -1.9750   -4.1026    0.1296    2.7383    0.7178    1.8209    0.3680    5.6274
-#> 26:    93.4057   -1.9316   -4.0922    0.1224    3.8103    0.7331    1.7796    0.3639    5.6861
-#> 27:    93.5013   -1.9188   -4.0698    0.0758    3.7127    0.7670    1.8750    0.3457    5.6624
-#> 28:    93.5703   -1.9523   -4.0758    0.0731    4.6390    0.7489    1.8583    0.3445    5.8077
-#> 29:    93.4694   -1.9559   -4.0566    0.0444    5.1290    0.8062    1.9344    0.3273    5.8688
-#> 30:    93.2290   -1.9824   -4.0475    0.0674    4.8726    0.8702    2.0343    0.3109    5.7579
-#> 31:    93.8652   -1.9771   -4.0510    0.0679    4.6289    0.8565    2.0529    0.2954    5.5526
-#> 32:    93.5854   -1.9573   -4.0510    0.0643    5.1320    0.8417    2.0138    0.2806    5.4199
-#> 33:    93.9870   -1.9503   -4.0513    0.0542    4.8754    0.8412    2.0433    0.2666    5.6945
-#> 34:    93.6884   -1.9172   -4.0633    0.0556    4.6317    0.8847    2.0861    0.2702    5.2687
-#> 35:    94.0375   -1.9365   -4.0576    0.0753    5.2320    0.8404    2.0791    0.2582    5.2760
-#> 36:    94.1588   -1.9423   -4.0499    0.0792    4.9704    0.8221    2.1145    0.2669    5.2050
-#> 37:    93.8626   -1.9356   -4.0538    0.0591    5.2723    0.8360    2.1407    0.2536    5.3218
-#> 38:    93.7237   -1.9357   -4.0611    0.0543    5.0087    0.8361    2.0788    0.2710    5.2866
-#> 39:    93.6513   -1.9327   -4.0408    0.0712    4.7582    0.8408    2.0051    0.2899    5.4693
-#> 40:    93.4619   -1.9634   -4.0360    0.1232    4.5203    0.8317    2.0367    0.3288    5.4324
-#> 41:    93.4809   -1.9601   -4.0351    0.1261    4.2943    0.8424    2.0081    0.3306    5.4573
-#> 42:    93.5851   -1.9745   -4.0428    0.1250    4.9744    0.8003    1.9818    0.3141    5.5168
-#> 43:    93.7820   -1.9597   -4.0401    0.1305    5.9118    0.7603    2.1332    0.2984    5.4899
-#> 44:    93.7419   -1.9509   -4.0495    0.1345    5.6162    0.7743    2.0459    0.2998    5.5344
-#> 45:    93.6967   -1.9366   -4.0522    0.1215    5.3354    0.7968    2.0566    0.2848    5.7738
-#> 46:    93.3665   -1.9553   -4.0018    0.0951    5.0686    0.7583    2.1124    0.2706    5.3850
-#> 47:    93.2974   -1.9332   -4.0091    0.0869    5.2792    0.8149    2.1009    0.2597    5.6743
-#> 48:    93.3967   -1.9540   -4.0218    0.0623    5.0152    0.8006    2.1538    0.2467    5.5889
-#> 49:    93.1652   -1.9724   -4.0350    0.0506    4.7645    0.8055    2.1445    0.2344    5.3586
-#> 50:    93.1464   -1.9377   -4.0185    0.0591    5.3658    0.8149    2.1523    0.2226    5.2483
-#> 51:    93.5217   -1.9246   -4.0272    0.0423    5.8579    0.8368    2.1596    0.2115    5.2746
-#> 52:    93.5512   -1.9257   -4.0204    0.0307    7.2345    0.8463    2.1903    0.2065    5.2405
-#> 53:    93.5400   -1.9428   -4.0300    0.0572    6.8728    0.8268    2.0807    0.2139    5.4127
-#> 54:    93.9868   -1.9502   -4.0129    0.0282    9.6651    0.8468    2.0823    0.2032    5.0396
-#> 55:    94.0505   -1.9393   -4.0073    0.0390   10.0994    0.8375    2.1018    0.2016    4.9147
-#> 56:    93.8010   -1.9493   -4.0026    0.0415   10.1741    0.8816    2.1117    0.2207    5.0723
-#> 57:    93.7596   -1.9762   -4.0154    0.0651    9.6654    0.8952    2.1662    0.2096    5.2311
-#> 58:    94.3399   -1.9353   -4.0095    0.0446    9.1821    0.9498    2.2103    0.1991    5.1009
-#> 59:    94.4036   -1.9283   -4.0279    0.0475    8.7230    0.9480    2.3209    0.1892    4.9930
-#> 60:    94.6395   -1.9260   -4.0348    0.0457    8.8651    0.9006    2.2565    0.1797    5.1751
-#> 61:    94.6499   -1.9291   -4.0216    0.0297    8.4218    0.9206    2.2220    0.1843    5.1124
-#> 62:    94.3847   -1.9010   -4.0300    0.0257    9.0591    0.9331    2.2795    0.1816    5.0834
-#> 63:    94.5510   -1.9120   -4.0116    0.0179    8.6061    0.9256    2.1791    0.1736    5.1513
-#> 64:    94.2510   -1.9213   -4.0184    0.0204    8.1758    0.9124    2.2131    0.1682    5.0698
-#> 65:    94.1173   -1.9044   -4.0279    0.0286    8.6773    0.9211    2.2202    0.1598    5.1120
-#> 66:    94.2093   -1.9098   -4.0206    0.0160    8.2435    0.9230    2.2475    0.1750    5.0175
-#> 67:    94.2814   -1.9339   -4.0041    0.0146    7.8313    0.9377    2.2350    0.1709    5.1478
-#> 68:    94.3001   -1.9079   -4.0127   -0.0103    7.4397    0.9163    2.2245    0.1640    5.2529
-#> 69:    94.3820   -1.9167   -4.0176    0.0296    7.0678    0.8704    2.2236    0.1888    5.2574
-#> 70:    94.2691   -1.9037   -4.0156    0.0388    6.7144    0.8601    2.1833    0.2128    5.0230
-#> 71:    94.3827   -1.9183   -4.0056    0.0485    6.3786    0.8491    2.2147    0.2345    5.1212
-#> 72:    94.3104   -1.9291   -4.0099    0.0330    6.0597    0.9007    2.2316    0.2255    5.3748
-#> 73:    94.1778   -1.9238   -4.0054    0.0222    5.7567    0.9479    2.2969    0.2142    5.2827
-#> 74:    94.1022   -1.9149   -4.0017    0.0497    5.4689    0.9305    2.3058    0.2035    5.3117
-#> 75:    94.2343   -1.9045   -4.0141    0.0189    5.1954    0.9141    2.3227    0.1933    5.1047
-#> 76:    94.0905   -1.9019   -4.0166    0.0170    5.5411    0.8978    2.3315    0.1836    5.1233
-#> 77:    94.2772   -1.9117   -4.0053    0.0584    5.2641    0.9238    2.3678    0.1866    4.9803
-#> 78:    94.7235   -1.9141   -4.0464    0.0758    5.0735    0.9308    2.3720    0.2062    5.0544
-#> 79:    94.4674   -1.9287   -4.0494    0.0724    5.7355    0.9063    2.3680    0.1959    5.0910
-#> 80:    93.9895   -1.9271   -4.0456    0.0366    7.2150    0.8857    2.4000    0.1861    5.0612
-#> 81:    94.3190   -1.9358   -4.0402    0.0506    7.5591    0.8891    2.3317    0.1814    4.8617
-#> 82:    94.1898   -1.9126   -4.0552    0.0595    7.6462    0.9157    2.3848    0.1854    4.7335
-#> 83:    94.2044   -1.9145   -4.0359    0.0295    7.8610    0.9451    2.4305    0.1871    4.9258
-#> 84:    93.8197   -1.9058   -3.9879   -0.0409   10.4218    0.9604    2.3848    0.2177    5.0619
-#> 85:    94.0219   -1.8957   -3.9753   -0.0441    9.9007    0.9637    2.4476    0.2219    5.0532
-#> 86:    94.0737   -1.8889   -3.9753   -0.0220    9.4056    0.9675    2.4476    0.2284    5.2694
-#> 87:    93.8548   -1.8755   -3.9707   -0.0024    8.9354    1.0066    2.4895    0.2340    5.4019
-#> 88:    93.7578   -1.9046   -3.9804   -0.0042    8.4886    0.9656    2.5006    0.2271    5.3724
-#> 89:    93.6848   -1.8936   -3.9689   -0.0396   10.6813    0.9805    2.4561    0.2254    5.2615
-#> 90:    93.3617   -1.9167   -3.9801   -0.0221   10.1472    1.0147    2.3589    0.2141    5.4193
-#> 91:    93.7419   -1.8964   -3.9888   -0.0363    9.6398    1.0077    2.3748    0.2066    5.3463
-#> 92:    93.8635   -1.8994   -3.9783   -0.0625    9.1578    1.0028    2.3282    0.2239    5.3026
-#> 93:    94.0864   -1.8648   -3.9426   -0.0813    8.8693    1.0348    2.3654    0.2127    5.2637
-#> 94:    93.9789   -1.8949   -3.9840   -0.0549   10.0871    1.0752    2.4551    0.2021    5.4225
-#> 95:    93.9008   -1.9141   -4.0080   -0.0644    9.8584    1.1599    2.4184    0.1920    5.2179
-#> 96:    93.6926   -2.0270   -3.8911   -0.0777   10.3968    1.1019    3.0518    0.1824    5.3163
-#> 97:    93.2478   -2.0074   -3.9034   -0.0427   10.7200    1.0468    2.9960    0.1732    5.5172
-#> 98:    93.4556   -2.0118   -3.9034   -0.0294   10.1840    1.0007    2.9960    0.1646    5.5887
-#> 99:    93.7548   -2.0076   -3.8894   -0.0157    9.7519    0.9507    3.0357    0.1569    5.7139
-#> 100:    93.8962   -2.0112   -3.8887   -0.0406    9.2643    0.9048    3.0369    0.1491    5.6145
-#> 101:    94.0889   -2.0221   -3.8612   -0.0145    8.8011    0.8728    3.1466    0.1499    5.4224
-#> 102:    94.5428   -2.0206   -3.8489    0.0115    8.3611    0.8292    3.1577    0.1473    5.6634
-#> 103:    94.4882   -2.0447   -3.8594    0.0514    7.9430    0.8202    3.1812    0.1562    5.5136
-#> 104:    94.3185   -2.0389   -3.8584    0.0258    8.3364    0.8346    3.1801    0.1484    5.3612
-#> 105:    94.2858   -2.0345   -3.8738   -0.0001   10.6008    0.8415    3.2251    0.1410    5.3359
-#> 106:    94.1264   -2.0415   -3.8756    0.0411   10.0707    0.8554    3.2182    0.1658    5.2280
-#> 107:    93.9801   -2.0574   -3.8674    0.0403   10.0269    0.8807    3.2628    0.1744    5.0299
-#> 108:    93.6911   -2.0295   -3.8693    0.0355    9.5255    0.8683    3.2708    0.1803    5.1880
-#> 109:    94.0646   -2.0260   -3.8806    0.0506    9.0493    0.8729    3.3140    0.1759    5.1927
-#> 110:    94.4591   -2.0378   -3.8962    0.0360    8.5968    0.8890    3.3076    0.1675    4.8961
-#> 111:    94.3748   -2.0319   -3.9053    0.0397    8.1670    0.8995    3.3254    0.1591    4.8066
-#> 112:    94.2370   -2.0338   -3.9017    0.0603    7.7586    0.8545    3.2484    0.1512    4.8856
-#> 113:    94.1242   -2.0237   -3.8954    0.0795    7.3707    0.8980    3.2127    0.1530    5.1859
-#> 114:    94.1452   -2.0298   -3.9197    0.0530    7.0021    0.8771    3.0744    0.1628    5.1303
-#> 115:    94.1403   -2.0410   -3.9093    0.0476    6.9173    0.9383    3.0223    0.1621    5.2563
-#> 116:    94.1612   -2.0424   -3.9063    0.0593    7.6367    0.8914    3.0420    0.1856    5.1566
-#> 117:    94.2018   -2.0488   -3.9041    0.0539    7.2549    0.8549    3.0204    0.1796    5.2119
-#> 118:    94.1315   -2.0579   -3.9139    0.0564    6.8922    0.8121    3.0180    0.1948    5.0302
-#> 119:    93.7398   -2.0747   -3.9202    0.0570    6.7510    0.7838    3.0084    0.1906    5.0863
-#> 120:    93.5945   -2.0511   -3.9388    0.0534    6.4134    0.7885    3.0100    0.2128    5.0597
-#> 121:    93.9845   -2.0613   -3.9338    0.0568    6.0928    0.7793    2.9944    0.2022    5.3179
-#> 122:    93.7779   -2.0831   -3.9338    0.0630    5.7881    0.7778    2.9944    0.1921    5.2399
-#> 123:    93.9128   -2.0623   -3.9135    0.0493    5.4987    0.8329    2.9729    0.1825    5.0752
-#> 124:    93.5190   -2.0804   -3.9315    0.0538    5.2238    0.8581    3.0220    0.1733    4.9713
-#> 125:    93.7427   -2.0649   -3.9309    0.0499    4.9626    0.8431    3.0260    0.1882    5.0718
-#> 126:    9.3540e+01  -2.0238e+00  -3.9006e+00  -6.8989e-05   4.7145e+00   8.3548e-01   2.9498e+00   1.9993e-01   5.2080e+00
-#> 127:    93.4310   -2.0496   -3.8898   -0.0173    4.4788    0.8864    2.9614    0.2302    5.6432
-#> 128:    93.7512   -2.0285   -3.9180   -0.0096    4.2548    0.8653    3.0768    0.2312    5.3906
-#> 129:    93.6908   -2.0718   -3.9113   -0.0194    4.0421    0.9022    3.0506    0.2386    5.3278
-#> 130:    93.5805   -1.9753   -4.0480    0.0065    3.8400    1.0388    2.8980    0.2276    5.2583
-#> 131:    93.8050   -1.9501   -4.0447    0.0040    3.8738    1.0957    2.7531    0.2162    5.3026
-#> 132:    93.6470   -1.9322   -4.0411    0.0048    3.6801    1.0618    2.6155    0.2159    5.2552
-#> 133:    94.2927   -1.9445   -4.0067   -0.0040    5.6903    1.0378    2.5425    0.2094    5.2430
-#> 134:    94.2814   -1.9286   -4.0021   -0.0144    6.9123    1.1316    2.5172    0.1990    5.3877
-#> 135:    94.0440   -1.9285   -4.0415    0.0254    6.5667    1.1416    2.4394    0.1975    5.3248
-#> 136:    94.0122   -1.9256   -4.0542    0.0156    6.6147    1.1511    2.4728    0.1954    5.2109
-#> 137:    93.8613   -1.9095   -4.0629   -0.0007    6.2840    1.1789    2.5078    0.2045    5.2876
-#> 138:    93.7410   -1.9345   -4.0788   -0.0005    6.0718    1.1507    2.5026    0.2086    5.3284
-#> 139:    93.6437   -1.9499   -4.0788    0.0159    5.7682    1.0932    2.5026    0.1982    5.4211
-#> 140:    93.4066   -1.9591   -4.0720    0.0472    6.9432    1.0883    2.4756    0.1947    5.4439
-#> 141:    93.6086   -1.9625   -4.1026    0.0785    7.7204    1.1027    2.3974    0.2084    5.6595
-#> 142:    93.8693   -1.9640   -4.1003    0.0670   10.1206    1.1196    2.2775    0.1980    5.4918
-#> 143:    93.6954   -1.9890   -4.0792    0.0824    9.6146    1.0636    2.3366    0.1881    5.2818
-#> 144:    93.5119   -1.9888   -4.0603    0.0645    9.1339    1.0557    2.3380    0.1787    5.3491
-#> 145:    93.3539   -1.9874   -4.0563    0.0764    8.6772    1.0340    2.3573    0.1697    5.4214
-#> 146:    93.2812   -1.9734   -4.0620    0.0674    8.4698    1.0504    2.3604    0.1641    5.5968
-#> 147:    93.8919   -1.9657   -4.0863    0.0596    8.0463    1.0288    2.4569    0.1668    5.3476
-#> 148:    93.7841   -1.9719   -4.0688    0.0880    9.4571    1.0719    2.4020    0.1692    5.1664
-#> 149:    93.6361   -1.9912   -4.0523    0.0895    8.9842    1.0183    2.5236    0.1671    5.5060
-#> 150:    93.6402   -1.9940   -4.0365    0.0730    9.1100    0.9674    2.3974    0.1669    5.5402
-#> 151:    93.4283   -1.9861   -4.0594    0.0805    8.6545    0.9567    2.4304    0.1652    5.3571
-#> 152:    93.7431   -1.9444   -4.0833    0.0612    9.2738    0.9789    2.3602    0.1571    5.0632
-#> 153:    93.7239   -1.9307   -4.0780    0.0780    8.9915    0.9995    2.3398    0.1600    5.1077
-#> 154:    94.0115   -1.9655   -4.0978    0.0859    9.0507    0.9894    2.3313    0.1628    5.2272
-#> 155:    94.3207   -1.9792   -4.0905    0.1114    8.5756    0.9988    2.3790    0.1873    5.0916
-#> 156:    94.3160   -1.9811   -4.0894    0.0906    5.0717    0.9968    2.3662    0.2003    4.9973
-#> 157:    94.3042   -1.9641   -4.1031    0.0966    5.1875    0.9911    2.3908    0.1943    4.9993
-#> 158:    94.0102   -1.9635   -4.1047    0.1003    5.2398    0.9834    2.3905    0.1809    5.2765
-#> 159:    94.5686   -2.0012   -4.1459    0.1212    6.8800    1.0317    2.5969    0.1215    5.3943
-#> 160:    94.2433   -1.9673   -4.1420    0.1165    8.0930    1.0286    2.5827    0.1092    5.2904
-#> 161:    94.1327   -1.9644   -4.1595    0.1196    9.5810    1.0786    2.7063    0.1123    5.1723
-#> 162:    94.0779   -1.9525   -4.1608    0.1103    6.6456    1.0562    2.7111    0.1277    5.0224
-#> 163:    94.0995   -1.9687   -4.1910    0.1320    8.2582    1.0701    2.8394    0.1232    5.1593
-#> 164:    94.4575   -1.9800   -4.1936    0.1208    6.4860    1.1603    2.8332    0.1254    5.1325
-#> 165:    94.3298   -1.9968   -4.1963    0.1506    5.7592    1.1484    2.9143    0.1196    5.3059
-#> 166:    94.2531   -1.9977   -4.1748    0.1566    5.3810    1.1262    2.8044    0.1142    5.2569
-#> 167:    94.4593   -1.9985   -4.1758    0.1435    7.0082    1.1247    2.8542    0.1125    5.4332
-#> 168:    94.0868   -2.0117   -4.2259    0.1345    7.5364    1.1395    3.0314    0.1137    5.2790
-#> 169:    93.7927   -2.0072   -4.2177    0.1276    6.7023    1.1292    3.0535    0.1135    5.1357
-#> 170:    93.8094   -2.0309   -4.2244    0.1298    6.7343    1.0975    3.2542    0.1065    5.2372
-#> 171:    93.7263   -2.0349   -4.2115    0.1204    8.2555    1.0626    3.2292    0.1020    5.4467
-#> 172:    93.3380   -2.0022   -4.2262    0.1193    6.6891    1.0822    3.2762    0.0989    5.3641
-#> 173:    93.5334   -2.0224   -4.2488    0.1145    6.0685    1.0328    3.4694    0.0978    5.4780
-#> 174:    93.1805   -2.0207   -4.2344    0.1025    6.1648    1.0612    3.2079    0.0976    5.2570
-#> 175:    93.3423   -2.0255   -4.1644    0.1070    5.9418    1.0701    2.8555    0.1059    5.3415
-#> 176:    93.3387   -2.0192   -4.1473    0.0786    4.7649    1.0508    2.9102    0.1101    5.3381
-#> 177:    93.4640   -2.0177   -4.1504    0.0709    4.5672    1.0590    2.9447    0.1103    5.3245
-#> 178:    93.4930   -2.0147   -4.1568    0.0777    4.5325    1.1063    2.7902    0.1247    5.2036
-#> 179:    93.7455   -2.0101   -4.1580    0.0823    4.2094    1.1020    2.8075    0.1246    5.1184
-#> 180:    93.4838   -1.9989   -4.1631    0.0868    3.6999    1.0782    2.8790    0.1280    5.2677
-#> 181:    93.5207   -1.9975   -4.1926    0.1013    4.5693    1.0706    2.9216    0.1375    5.3783
-#> 182:    93.6695   -2.0251   -4.1717    0.0809    3.8373    1.0341    2.9954    0.1328    5.3774
-#> 183:    93.7238   -2.0095   -4.1222    0.0861    3.8354    1.0138    2.7536    0.1512    5.2600
-#> 184:    93.7106   -2.0032   -4.1244    0.0853    4.1968    1.0250    2.6849    0.1590    5.1996
-#> 185:    93.2862   -2.0028   -4.1628    0.0743    5.4347    1.0373    2.6528    0.1640    5.3269
-#> 186:    93.5567   -2.0040   -4.1438    0.0807    6.5150    1.0562    2.6486    0.1589    5.4158
-#> 187:    93.7894   -2.0023   -4.1137    0.1288    5.1401    1.0207    2.5217    0.1745    5.6484
-#> 188:    93.4911   -1.8872   -4.2405    0.1324    4.3165    0.8176    2.2483    0.1870    5.5214
-#> 189:    93.9184   -1.8982   -4.2936    0.1606    3.7995    0.8383    2.2555    0.1766    5.6320
-#> 190:    93.7487   -1.8878   -4.2872    0.1651    3.6764    0.8860    2.2088    0.1748    5.4829
-#> 191:    93.8940   -1.8715   -4.3244    0.1650    2.8119    0.9024    2.1141    0.1903    5.7768
-#> 192:    93.9378   -1.9105   -4.3010    0.1954    2.5239    0.8232    2.1331    0.1831    5.8507
-#> 193:    94.5609   -1.8766   -4.3303    0.2042    3.9595    0.8413    2.0662    0.2095    5.6119
-#> 194:    94.7465   -1.9036   -4.3363    0.2112    5.0784    0.8176    2.1071    0.2149    5.6051
-#> 195:    94.4761   -1.8852   -4.3375    0.2021    4.7026    0.7615    2.0556    0.2333    5.3997
-#> 196:    93.7678   -1.9037   -4.3676    0.2273    5.6976    0.7824    2.1487    0.2478    5.2531
-#> 197:    94.0788   -1.9208   -4.3670    0.2203    3.8352    0.7644    2.0893    0.2354    5.2196
-#> 198:    94.3424   -1.8825   -4.3288    0.2075    4.9447    0.7304    1.9525    0.2502    5.1387
-#> 199:    94.0613   -1.9911   -4.1676    0.2379    3.6248    0.6126    2.8184    0.2801    5.3421
-#> 200:    94.4814   -2.0045   -4.1782    0.2245    3.5637    0.6427    2.7132    0.3014    5.3984
-#> 201:    94.3903   -1.9973   -4.1773    0.2165    3.4686    0.6525    2.7040    0.2901    5.4178
-#> 202:    94.1840   -1.9928   -4.1742    0.2117    3.6920    0.6576    2.7046    0.2870    5.3743
-#> 203:    94.1832   -1.9865   -4.1670    0.2025    3.8180    0.6618    2.7097    0.2758    5.3389
-#> 204:    94.1550   -1.9832   -4.1631    0.1955    3.9449    0.6613    2.6998    0.2691    5.2948
-#> 205:    94.1853   -1.9824   -4.1602    0.1948    4.1753    0.6598    2.6909    0.2695    5.2556
-#> 206:    94.1775   -1.9800   -4.1564    0.1918    4.1962    0.6581    2.6778    0.2678    5.2316
-#> 207:    94.1754   -1.9736   -4.1532    0.1864    4.2107    0.6580    2.6645    0.2694    5.2553
-#> 208:    94.1591   -1.9695   -4.1498    0.1811    4.2621    0.6596    2.6537    0.2712    5.2543
-#> 209:    94.1225   -1.9675   -4.1454    0.1744    4.1977    0.6651    2.6519    0.2687    5.3075
-#> 210:    94.1047   -1.9628   -4.1424    0.1666    4.1981    0.6663    2.6570    0.2717    5.3160
-#> 211:    94.1161   -1.9587   -4.1398    0.1600    4.1858    0.6674    2.6614    0.2728    5.3307
-#> 212:    94.0976   -1.9551   -4.1379    0.1529    4.2002    0.6693    2.6737    0.2709    5.3288
-#> 213:    94.0845   -1.9511   -4.1365    0.1449    4.1381    0.6710    2.6727    0.2680    5.3322
-#> 214:    94.0582   -1.9493   -4.1351    0.1394    4.0630    0.6733    2.6729    0.2663    5.3504
-#> 215:    94.0449   -1.9493   -4.1338    0.1340    3.9607    0.6733    2.6719    0.2641    5.3681
-#> 216:    94.0030   -1.9496   -4.1321    0.1299    4.0200    0.6742    2.6727    0.2622    5.3619
-#> 217:    93.9560   -1.9514   -4.1315    0.1267    4.0642    0.6778    2.6764    0.2612    5.3584
-#> 218:    93.9485   -1.9520   -4.1297    0.1235    4.1822    0.6795    2.6745    0.2599    5.3471
-#> 219:    93.9650   -1.9523   -4.1289    0.1211    4.3244    0.6807    2.6851    0.2591    5.3531
-#> 220:    93.9961   -1.9519   -4.1284    0.1193    4.4276    0.6837    2.6936    0.2577    5.3528
-#> 221:    94.0080   -1.9517   -4.1275    0.1183    4.5303    0.6866    2.6979    0.2578    5.3538
-#> 222:    94.0143   -1.9505   -4.1272    0.1159    4.5882    0.6887    2.7039    0.2570    5.3489
-#> 223:    94.0189   -1.9491   -4.1269    0.1138    4.5674    0.6910    2.7092    0.2562    5.3424
-#> 224:    94.0136   -1.9464   -4.1270    0.1126    4.5582    0.6923    2.7161    0.2548    5.3421
-#> 225:    94.0118   -1.9444   -4.1276    0.1112    4.6000    0.6929    2.7269    0.2533    5.3525
-#> 226:    93.9884   -1.9428   -4.1260    0.1099    4.6720    0.6935    2.7428    0.2530    5.3427
-#> 227:    93.9657   -1.9416   -4.1247    0.1097    4.7197    0.6937    2.7581    0.2529    5.3455
-#> 228:    93.9586   -1.9410   -4.1234    0.1105    4.7731    0.6945    2.7801    0.2528    5.3408
-#> 229:    93.9574   -1.9409   -4.1215    0.1102    4.7898    0.6963    2.7970    0.2518    5.3366
-#> 230:    93.9495   -1.9410   -4.1201    0.1096    4.7966    0.6982    2.8117    0.2505    5.3301
-#> 231:    93.9378   -1.9416   -4.1193    0.1093    4.7947    0.6993    2.8274    0.2492    5.3270
-#> 232:    93.9362   -1.9421   -4.1184    0.1086    4.8132    0.7011    2.8411    0.2477    5.3191
-#> 233:    93.9412   -1.9424   -4.1167    0.1074    4.8188    0.7028    2.8514    0.2459    5.3134
-#> 234:    93.9436   -1.9424   -4.1152    0.1061    4.7865    0.7040    2.8618    0.2440    5.3153
-#> 235:    93.9413   -1.9425   -4.1134    0.1051    4.8017    0.7062    2.8679    0.2426    5.3137
-#> 236:    93.9480   -1.9423   -4.1119    0.1033    4.8537    0.7085    2.8730    0.2416    5.3089
-#> 237:    93.9560   -1.9408   -4.1105    0.1020    4.9091    0.7098    2.8777    0.2411    5.2970
-#> 238:    93.9610   -1.9393   -4.1091    0.1003    4.9394    0.7113    2.8824    0.2409    5.2902
-#> 239:    93.9634   -1.9378   -4.1080    0.0993    4.9304    0.7121    2.8875    0.2407    5.2868
-#> 240:    93.9727   -1.9360   -4.1063    0.0980    4.9651    0.7128    2.8918    0.2404    5.2825
-#> 241:    93.9736   -1.9348   -4.1045    0.0969    5.0080    0.7139    2.8917    0.2395    5.2751
-#> 242:    93.9779   -1.9334   -4.1030    0.0959    5.0856    0.7150    2.8923    0.2389    5.2656
-#> 243:    93.9807   -1.9322   -4.1015    0.0953    5.1490    0.7158    2.8929    0.2385    5.2560
-#> 244:    93.9858   -1.9317   -4.0998    0.0942    5.2172    0.7171    2.8922    0.2380    5.2514
-#> 245:    93.9798   -1.9309   -4.0984    0.0920    5.2903    0.7172    2.8892    0.2383    5.2502
-#> 246:    93.9782   -1.9296   -4.0971    0.0903    5.3132    0.7180    2.8866    0.2384    5.2482
-#> 247:    93.9809   -1.9290   -4.0958    0.0886    5.3342    0.7188    2.8839    0.2386    5.2466
-#> 248:    93.9731   -1.9281   -4.0944    0.0873    5.3438    0.7187    2.8812    0.2393    5.2480
-#> 249:    93.9594   -1.9273   -4.0932    0.0852    5.3449    0.7181    2.8781    0.2401    5.2489
-#> 250:    93.9508   -1.9261   -4.0919    0.0835    5.3194    0.7173    2.8752    0.2406    5.2495
-#> 251:    93.9421   -1.9248   -4.0903    0.0812    5.3051    0.7180    2.8714    0.2410    5.2480
-#> 252:    93.9291   -1.9240   -4.0888    0.0793    5.3122    0.7175    2.8681    0.2415    5.2447
-#> 253:    93.9233   -1.9232   -4.0876    0.0777    5.3289    0.7170    2.8636    0.2420    5.2423
-#> 254:    93.9189   -1.9217   -4.0863    0.0760    5.3708    0.7165    2.8593    0.2425    5.2395
-#> 255:    93.9130   -1.9205   -4.0850    0.0743    5.4093    0.7157    2.8548    0.2428    5.2393
-#> 256:    93.9031   -1.9195   -4.0837    0.0731    5.4400    0.7153    2.8501    0.2432    5.2417
-#> 257:    93.9079   -1.9183   -4.0821    0.0720    5.4612    0.7138    2.8454    0.2434    5.2469
-#> 258:    93.9117   -1.9173   -4.0807    0.0711    5.4979    0.7126    2.8412    0.2439    5.2491
-#> 259:    93.9199   -1.9164   -4.0797    0.0708    5.5145    0.7107    2.8364    0.2449    5.2481
-#> 260:    93.9300   -1.9150   -4.0782    0.0699    5.5067    0.7086    2.8316    0.2453    5.2501
-#> 261:    93.9382   -1.9140   -4.0768    0.0689    5.5191    0.7070    2.8271    0.2455    5.2518
-#> 262:    93.9467   -1.9126   -4.0755    0.0681    5.5261    0.7049    2.8227    0.2454    5.2564
-#> 263:    93.9594   -1.9110   -4.0739    0.0667    5.5365    0.7039    2.8196    0.2455    5.2613
-#> 264:    93.9697   -1.9096   -4.0718    0.0650    5.5589    0.7033    2.8174    0.2459    5.2628
-#> 265:    93.9784   -1.9080   -4.0698    0.0631    5.5668    0.7025    2.8153    0.2458    5.2627
-#> 266:    93.9865   -1.9068   -4.0686    0.0615    5.5819    0.7012    2.8114    0.2456    5.2638
-#> 267:    93.9940   -1.9055   -4.0673    0.0599    5.5887    0.7000    2.8076    0.2452    5.2644
-#> 268:    93.9991   -1.9045   -4.0660    0.0584    5.5989    0.6986    2.8039    0.2453    5.2657
-#> 269:    94.0034   -1.9036   -4.0649    0.0573    5.6276    0.6972    2.7990    0.2453    5.2648
-#> 270:    94.0104   -1.9028   -4.0639    0.0561    5.6456    0.6959    2.7945    0.2453    5.2614
-#> 271:    94.0190   -1.9022   -4.0629    0.0550    5.6409    0.6950    2.7900    0.2451    5.2606
-#> 272:    94.0244   -1.9017   -4.0623    0.0542    5.6452    0.6944    2.7863    0.2449    5.2626
-#> 273:    94.0312   -1.9010   -4.0620    0.0531    5.6581    0.6939    2.7821    0.2450    5.2620
-#> 274:    94.0387   -1.9004   -4.0615    0.0520    5.6569    0.6932    2.7774    0.2456    5.2657
-#> 275:    94.0381   -1.9000   -4.0611    0.0510    5.6525    0.6938    2.7727    0.2463    5.2662
-#> 276:    94.0426   -1.8994   -4.0606    0.0498    5.6664    0.6955    2.7682    0.2472    5.2687
-#> 277:    94.0437   -1.8988   -4.0604    0.0486    5.6705    0.6969    2.7646    0.2479    5.2699
-#> 278:    94.0470   -1.8982   -4.0606    0.0476    5.6495    0.6983    2.7620    0.2487    5.2741
-#> 279:    94.0475   -1.8980   -4.0608    0.0470    5.6561    0.6990    2.7590    0.2494    5.2749
-#> 280:    94.0485   -1.8977   -4.0609    0.0462    5.6510    0.6997    2.7565    0.2501    5.2755
-#> 281:    94.0473   -1.8975   -4.0609    0.0456    5.6493    0.6998    2.7529    0.2504    5.2764
-#> 282:    94.0448   -1.8972   -4.0608    0.0448    5.6523    0.7003    2.7495    0.2506    5.2773
-#> 283:    94.0392   -1.8975   -4.0608    0.0440    5.6543    0.7011    2.7463    0.2507    5.2772
-#> 284:    94.0315   -1.8976   -4.0609    0.0432    5.6575    0.7017    2.7431    0.2506    5.2792
-#> 285:    94.0262   -1.8980   -4.0611    0.0427    5.6632    0.7018    2.7402    0.2505    5.2805
-#> 286:    94.0255   -1.8986   -4.0615    0.0427    5.6683    0.7018    2.7371    0.2507    5.2795
-#> 287:    94.0234   -1.8992   -4.0619    0.0427    5.6533    0.7014    2.7340    0.2513    5.2803
-#> 288:    94.0227   -1.9000   -4.0631    0.0431    5.6485    0.7016    2.7352    0.2517    5.2802
-#> 289:    94.0179   -1.9008   -4.0641    0.0433    5.6553    0.7016    2.7358    0.2523    5.2808
-#> 290:    94.0135   -1.9017   -4.0650    0.0435    5.6776    0.7015    2.7363    0.2528    5.2839
-#> 291:    94.0101   -1.9025   -4.0660    0.0440    5.7028    0.7012    2.7372    0.2531    5.2883
-#> 292:    94.0066   -1.9034   -4.0672    0.0442    5.7277    0.7007    2.7369    0.2536    5.2890
-#> 293:    94.0002   -1.9042   -4.0681    0.0441    5.7462    0.7004    2.7366    0.2538    5.2906
-#> 294:    93.9917   -1.9049   -4.0690    0.0440    5.7707    0.7001    2.7363    0.2539    5.2927
-#> 295:    93.9864   -1.9055   -4.0703    0.0440    5.7816    0.7001    2.7362    0.2542    5.2950
-#> 296:    93.9807   -1.9060   -4.0716    0.0441    5.7884    0.7000    2.7362    0.2545    5.2974
-#> 297:    93.9749   -1.9063   -4.0729    0.0442    5.7926    0.7005    2.7362    0.2548    5.3032
-#> 298:    93.9700   -1.9070   -4.0735    0.0442    5.7850    0.7005    2.7323    0.2553    5.3067
-#> 299:    93.9668   -1.9075   -4.0740    0.0442    5.7688    0.7000    2.7293    0.2558    5.3100
-#> 300:    93.9654   -1.9080   -4.0742    0.0441    5.7541    0.6993    2.7260    0.2563    5.3123
-#> 301:    93.9678   -1.9082   -4.0744    0.0439    5.7383    0.6980    2.7217    0.2568    5.3165
-#> 302:    93.9687   -1.9087   -4.0747    0.0435    5.7262    0.6977    2.7175    0.2574    5.3179
-#> 303:    93.9675   -1.9090   -4.0751    0.0430    5.7050    0.6966    2.7137    0.2580    5.3197
-#> 304:    93.9641   -1.9092   -4.0755    0.0428    5.6977    0.6954    2.7097    0.2583    5.3215
-#> 305:    93.9624   -1.9095   -4.0759    0.0427    5.6986    0.6947    2.7061    0.2585    5.3200
-#> 306:    93.9623   -1.9098   -4.0763    0.0428    5.7065    0.6941    2.7025    0.2587    5.3174
-#> 307:    93.9635   -1.9105   -4.0767    0.0430    5.7229    0.6938    2.6992    0.2585    5.3153
-#> 308:    93.9658   -1.9112   -4.0778    0.0435    5.7340    0.6935    2.6992    0.2580    5.3131
-#> 309:    93.9671   -1.9119   -4.0784    0.0440    5.7510    0.6929    2.6990    0.2576    5.3113
-#> 310:    93.9669   -1.9124   -4.0791    0.0441    5.7560    0.6926    2.6988    0.2569    5.3128
-#> 311:    93.9670   -1.9129   -4.0795    0.0443    5.7557    0.6922    2.6972    0.2563    5.3134
-#> 312:    93.9689   -1.9132   -4.0799    0.0446    5.7554    0.6921    2.6959    0.2559    5.3125
-#> 313:    93.9685   -1.9136   -4.0806    0.0448    5.7489    0.6921    2.6960    0.2553    5.3110
-#> 314:    93.9673   -1.9138   -4.0812    0.0447    5.7562    0.6925    2.6964    0.2545    5.3107
-#> 315:    93.9635   -1.9139   -4.0818    0.0447    5.7392    0.6931    2.6971    0.2539    5.3127
-#> 316:    93.9581   -1.9139   -4.0823    0.0442    5.7376    0.6937    2.6974    0.2532    5.3140
-#> 317:    93.9541   -1.9140   -4.0826    0.0437    5.7426    0.6946    2.6968    0.2526    5.3155
-#> 318:    93.9521   -1.9141   -4.0829    0.0432    5.7378    0.6951    2.6970    0.2521    5.3158
-#> 319:    93.9520   -1.9139   -4.0829    0.0423    5.7366    0.6959    2.6977    0.2516    5.3138
-#> 320:    93.9538   -1.9136   -4.0828    0.0414    5.7416    0.6964    2.6980    0.2510    5.3135
-#> 321:    93.9557   -1.9132   -4.0827    0.0406    5.7539    0.6969    2.6983    0.2503    5.3141
-#> 322:    93.9568   -1.9130   -4.0825    0.0399    5.7460    0.6971    2.6988    0.2497    5.3155
-#> 323:    93.9594   -1.9125   -4.0824    0.0393    5.7274    0.6972    2.6993    0.2492    5.3166
-#> 324:    93.9608   -1.9122   -4.0823    0.0386    5.7161    0.6973    2.7006    0.2487    5.3156
-#> 325:    93.9601   -1.9120   -4.0822    0.0379    5.7036    0.6973    2.7019    0.2483    5.3161
-#> 326:    93.9602   -1.9118   -4.0822    0.0372    5.6817    0.6977    2.7023    0.2480    5.3182
-#> 327:    93.9615   -1.9115   -4.0820    0.0364    5.6682    0.6986    2.7024    0.2476    5.3203
-#> 328:    93.9601   -1.9114   -4.0814    0.0355    5.6746    0.6999    2.7012    0.2472    5.3224
-#> 329:    93.9580   -1.9112   -4.0809    0.0348    5.6670    0.7014    2.7003    0.2469    5.3229
-#> 330:    93.9577   -1.9111   -4.0808    0.0341    5.6613    0.7023    2.7007    0.2466    5.3224
-#> 331:    93.9570   -1.9109   -4.0808    0.0334    5.6607    0.7029    2.7020    0.2463    5.3223
-#> 332:    93.9599   -1.9106   -4.0806    0.0328    5.6610    0.7037    2.7023    0.2459    5.3212
-#> 333:    93.9638   -1.9102   -4.0806    0.0320    5.6751    0.7043    2.7029    0.2458    5.3187
-#> 334:    93.9672   -1.9096   -4.0805    0.0311    5.6801    0.7051    2.7033    0.2456    5.3168
-#> 335:    93.9714   -1.9093   -4.0805    0.0302    5.6855    0.7058    2.7038    0.2453    5.3156
-#> 336:    93.9755   -1.9090   -4.0804    0.0294    5.6979    0.7062    2.7040    0.2452    5.3158
-#> 337:    93.9796   -1.9088   -4.0803    0.0286    5.7025    0.7069    2.7038    0.2447    5.3159
-#> 338:    93.9845   -1.9087   -4.0803    0.0278    5.7100    0.7074    2.7042    0.2443    5.3166
-#> 339:    93.9889   -1.9084   -4.0803    0.0273    5.7123    0.7080    2.7045    0.2438    5.3165
-#> 340:    93.9916   -1.9082   -4.0801    0.0267    5.7289    0.7086    2.7045    0.2434    5.3167
-#> 341:    93.9938   -1.9080   -4.0800    0.0263    5.7602    0.7091    2.7048    0.2430    5.3173
-#> 342:    93.9971   -1.9076   -4.0799    0.0257    5.7951    0.7096    2.7046    0.2427    5.3171
-#> 343:    93.9979   -1.9073   -4.0794    0.0251    5.8156    0.7101    2.7044    0.2424    5.3157
-#> 344:    94.0015   -1.9070   -4.0792    0.0246    5.8378    0.7105    2.7047    0.2420    5.3153
-#> 345:    94.0040   -1.9067   -4.0789    0.0241    5.8559    0.7111    2.7046    0.2414    5.3149
-#> 346:    94.0073   -1.9066   -4.0787    0.0237    5.8810    0.7119    2.7045    0.2409    5.3131
-#> 347:    94.0084   -1.9066   -4.0785    0.0232    5.8815    0.7127    2.7044    0.2406    5.3125
-#> 348:    94.0084   -1.9067   -4.0785    0.0229    5.8870    0.7132    2.7051    0.2403    5.3110
-#> 349:    94.0079   -1.9068   -4.0785    0.0225    5.8882    0.7136    2.7048    0.2401    5.3127
-#> 350:    94.0075   -1.9067   -4.0785    0.0220    5.8857    0.7137    2.7045    0.2396    5.3133
-#> 351:    94.0068   -1.9068   -4.0786    0.0218    5.8849    0.7140    2.7041    0.2393    5.3135
-#> 352:    94.0059   -1.9067   -4.0788    0.0216    5.8778    0.7141    2.7039    0.2390    5.3139
-#> 353:    94.0073   -1.9067   -4.0792    0.0215    5.8709    0.7140    2.7047    0.2388    5.3129
-#> 354:    94.0078   -1.9065   -4.0795    0.0214    5.8623    0.7139    2.7054    0.2386    5.3135
-#> 355:    94.0065   -1.9064   -4.0795    0.0211    5.8637    0.7137    2.7048    0.2383    5.3122
-#> 356:    94.0080   -1.9063   -4.0796    0.0209    5.8613    0.7134    2.7041    0.2380    5.3121
-#> 357:    94.0105   -1.9061   -4.0797    0.0206    5.8613    0.7132    2.7036    0.2379    5.3119
-#> 358:    94.0114   -1.9059   -4.0798    0.0205    5.8539    0.7130    2.7029    0.2377    5.3107
-#> 359:    94.0154   -1.9058   -4.0799    0.0203    5.8559    0.7126    2.7024    0.2374    5.3112
-#> 360:    94.0165   -1.9057   -4.0800    0.0201    5.8544    0.7124    2.7020    0.2372    5.3099
-#> 361:    94.0198   -1.9056   -4.0802    0.0199    5.8511    0.7121    2.7018    0.2370    5.3089
-#> 362:    94.0224   -1.9054   -4.0811    0.0198    5.8509    0.7122    2.7071    0.2368    5.3077
-#> 363:    94.0241   -1.9053   -4.0821    0.0197    5.8582    0.7121    2.7135    0.2366    5.3073
-#> 364:    94.0254   -1.9052   -4.0824    0.0195    5.8606    0.7122    2.7147    0.2362    5.3079
-#> 365:    94.0276   -1.9052   -4.0831    0.0195    5.8668    0.7119    2.7197    0.2359    5.3081
-#> 366:    94.0276   -1.9052   -4.0836    0.0195    5.8765    0.7121    2.7217    0.2357    5.3074
-#> 367:    94.0276   -1.9051   -4.0842    0.0194    5.8627    0.7120    2.7240    0.2354    5.3083
-#> 368:    94.0292   -1.9050   -4.0847    0.0195    5.8579    0.7120    2.7254    0.2352    5.3096
-#> 369:    94.0289   -1.9049   -4.0852    0.0195    5.8590    0.7122    2.7271    0.2350    5.3095
-#> 370:    94.0300   -1.9049   -4.0855    0.0194    5.8712    0.7123    2.7284    0.2348    5.3094
-#> 371:    94.0309   -1.9050   -4.0858    0.0194    5.8766    0.7122    2.7295    0.2346    5.3095
-#> 372:    94.0306   -1.9050   -4.0860    0.0196    5.8800    0.7121    2.7306    0.2344    5.3101
-#> 373:    94.0315   -1.9051   -4.0861    0.0196    5.8840    0.7120    2.7305    0.2341    5.3091
-#> 374:    94.0323   -1.9052   -4.0862    0.0194    5.8755    0.7120    2.7301    0.2337    5.3101
-#> 375:    94.0344   -1.9055   -4.0863    0.0193    5.8744    0.7122    2.7308    0.2333    5.3121
-#> 376:    94.0341   -1.9056   -4.0865    0.0191    5.8738    0.7122    2.7311    0.2327    5.3136
-#> 377:    94.0320   -1.9055   -4.0868    0.0188    5.8703    0.7121    2.7311    0.2322    5.3161
-#> 378:    94.0291   -1.9058   -4.0869    0.0186    5.8771    0.7124    2.7311    0.2317    5.3187
-#> 379:    94.0273   -1.9062   -4.0872    0.0184    5.8829    0.7127    2.7316    0.2312    5.3206
-#> 380:    94.0259   -1.9067   -4.0875    0.0181    5.8786    0.7130    2.7321    0.2306    5.3235
-#> 381:    94.0231   -1.9068   -4.0877    0.0178    5.8716    0.7132    2.7331    0.2300    5.3231
-#> 382:    94.0210   -1.9069   -4.0879    0.0172    5.8636    0.7134    2.7340    0.2294    5.3240
-#> 383:    94.0189   -1.9070   -4.0880    0.0167    5.8596    0.7140    2.7351    0.2287    5.3246
-#> 384:    94.0171   -1.9070   -4.0882    0.0161    5.8588    0.7147    2.7365    0.2281    5.3251
-#> 385:    94.0141   -1.9070   -4.0880    0.0154    5.8659    0.7152    2.7365    0.2276    5.3263
-#> 386:    94.0116   -1.9070   -4.0879    0.0148    5.8785    0.7158    2.7364    0.2270    5.3272
-#> 387:    94.0090   -1.9070   -4.0877    0.0142    5.8874    0.7164    2.7363    0.2264    5.3286
-#> 388:    94.0068   -1.9069   -4.0875    0.0136    5.9016    0.7169    2.7364    0.2258    5.3299
-#> 389:    94.0063   -1.9067   -4.0873    0.0131    5.9114    0.7175    2.7363    0.2253    5.3332
-#> 390:    94.0074   -1.9064   -4.0872    0.0126    5.9258    0.7175    2.7362    0.2249    5.3353
-#> 391:    94.0092   -1.9061   -4.0870    0.0121    5.9426    0.7174    2.7359    0.2245    5.3370
-#> 392:    94.0112   -1.9060   -4.0870    0.0119    5.9499    0.7175    2.7358    0.2242    5.3375
-#> 393:    94.0120   -1.9058   -4.0869    0.0116    5.9514    0.7177    2.7351    0.2237    5.3364
-#> 394:    94.0137   -1.9056   -4.0867    0.0112    5.9560    0.7179    2.7342    0.2234    5.3371
-#> 395:    94.0150   -1.9054   -4.0866    0.0109    5.9566    0.7184    2.7340    0.2229    5.3376
-#> 396:    94.0175   -1.9054   -4.0866    0.0106    5.9564    0.7189    2.7341    0.2226    5.3370
-#> 397:    94.0195   -1.9055   -4.0866    0.0104    5.9447    0.7193    2.7344    0.2223    5.3378
-#> 398:    94.0201   -1.9056   -4.0867    0.0102    5.9353    0.7197    2.7348    0.2220    5.3380
-#> 399:    94.0204   -1.9056   -4.0868    0.0101    5.9282    0.7201    2.7350    0.2217    5.3387
-#> 400:    94.0198   -1.9058   -4.0867    0.0099    5.9243    0.7206    2.7348    0.2214    5.3383
-#> 401:    94.0194   -1.9059   -4.0867    0.0097    5.9225    0.7210    2.7345    0.2211    5.3379
-#> 402:    94.0176   -1.9060   -4.0868    0.0096    5.9237    0.7215    2.7342    0.2209    5.3370
-#> 403:    94.0172   -1.9061   -4.0869    0.0095    5.9259    0.7220    2.7337    0.2206    5.3371
-#> 404:    94.0147   -1.9062   -4.0870    0.0093    5.9322    0.7226    2.7330    0.2203    5.3382
-#> 405:    94.0131   -1.9065   -4.0872    0.0092    5.9354    0.7232    2.7326    0.2202    5.3385
-#> 406:    94.0117   -1.9066   -4.0872    0.0091    5.9399    0.7237    2.7318    0.2200    5.3388
-#> 407:    94.0114   -1.9069   -4.0871    0.0090    5.9495    0.7238    2.7314    0.2199    5.3397
-#> 408:    94.0133   -1.9071   -4.0870    0.0089    5.9505    0.7238    2.7310    0.2197    5.3401
-#> 409:    94.0159   -1.9074   -4.0868    0.0090    5.9523    0.7237    2.7309    0.2196    5.3417
-#> 410:    94.0171   -1.9076   -4.0864    0.0087    5.9503    0.7235    2.7307    0.2195    5.3449
-#> 411:    94.0193   -1.9078   -4.0862    0.0086    5.9528    0.7234    2.7304    0.2194    5.3476
-#> 412:    94.0193   -1.9082   -4.0860    0.0088    5.9516    0.7236    2.7303    0.2195    5.3509
-#> 413:    94.0192   -1.9085   -4.0859    0.0087    5.9491    0.7235    2.7302    0.2195    5.3517
-#> 414:    94.0175   -1.9086   -4.0860    0.0087    5.9453    0.7237    2.7297    0.2196    5.3523
-#> 415:    94.0156   -1.9088   -4.0861    0.0088    5.9408    0.7238    2.7289    0.2196    5.3528
-#> 416:    94.0145   -1.9090   -4.0861    0.0088    5.9442    0.7236    2.7281    0.2197    5.3540
-#> 417:    94.0140   -1.9093   -4.0862    0.0092    5.9459    0.7235    2.7274    0.2198    5.3549
-#> 418:    94.0144   -1.9097   -4.0864    0.0095    5.9495    0.7233    2.7269    0.2199    5.3551
-#> 419:    94.0142   -1.9102   -4.0866    0.0099    5.9425    0.7233    2.7265    0.2200    5.3555
-#> 420:    94.0134   -1.9107   -4.0867    0.0102    5.9338    0.7234    2.7260    0.2200    5.3563
-#> 421:    94.0096   -1.9113   -4.0869    0.0105    5.9272    0.7236    2.7260    0.2200    5.3571
-#> 422:    94.0069   -1.9118   -4.0872    0.0108    5.9238    0.7238    2.7261    0.2200    5.3576
-#> 423:    94.0034   -1.9124   -4.0874    0.0111    5.9217    0.7240    2.7260    0.2200    5.3579
-#> 424:    94.0009   -1.9129   -4.0876    0.0114    5.9258    0.7240    2.7259    0.2200    5.3578
-#> 425:    94.0000   -1.9134   -4.0879    0.0119    5.9330    0.7240    2.7258    0.2199    5.3572
-#> 426:    93.9991   -1.9138   -4.0881    0.0122    5.9526    0.7243    2.7256    0.2198    5.3572
-#> 427:    93.9969   -1.9140   -4.0882    0.0124    5.9692    0.7247    2.7258    0.2196    5.3587
-#> 428:    93.9940   -1.9143   -4.0883    0.0124    5.9777    0.7247    2.7259    0.2194    5.3591
-#> 429:    93.9935   -1.9145   -4.0882    0.0123    5.9781    0.7247    2.7260    0.2192    5.3601
-#> 430:    93.9925   -1.9147   -4.0881    0.0122    5.9772    0.7247    2.7260    0.2190    5.3606
-#> 431:    93.9928   -1.9150   -4.0879    0.0120    5.9824    0.7249    2.7262    0.2189    5.3616
-#> 432:    93.9930   -1.9152   -4.0879    0.0120    5.9797    0.7251    2.7267    0.2188    5.3618
-#> 433:    93.9930   -1.9154   -4.0878    0.0119    5.9785    0.7254    2.7271    0.2187    5.3626
-#> 434:    93.9930   -1.9156   -4.0878    0.0120    5.9711    0.7255    2.7273    0.2186    5.3638
-#> 435:    93.9935   -1.9157   -4.0878    0.0120    5.9659    0.7255    2.7269    0.2186    5.3643
-#> 436:    93.9951   -1.9158   -4.0876    0.0120    5.9570    0.7253    2.7263    0.2184    5.3667
-#> 437:    93.9980   -1.9158   -4.0874    0.0119    5.9492    0.7252    2.7259    0.2182    5.3680
-#> 438:    93.9999   -1.9158   -4.0872    0.0117    5.9361    0.7250    2.7255    0.2179    5.3700
-#> 439:    93.9990   -1.9159   -4.0868    0.0115    5.9312    0.7249    2.7247    0.2177    5.3700
-#> 440:    93.9986   -1.9160   -4.0865    0.0114    5.9280    0.7248    2.7235    0.2175    5.3698
-#> 441:    93.9996   -1.9160   -4.0863    0.0114    5.9248    0.7246    2.7222    0.2173    5.3696
-#> 442:    94.0001   -1.9160   -4.0861    0.0114    5.9266    0.7243    2.7213    0.2171    5.3702
-#> 443:    94.0004   -1.9159   -4.0859    0.0113    5.9228    0.7241    2.7202    0.2169    5.3707
-#> 444:    93.9989   -1.9161   -4.0858    0.0113    5.9200    0.7239    2.7194    0.2166    5.3722
-#> 445:    93.9971   -1.9162   -4.0857    0.0114    5.9257    0.7238    2.7182    0.2165    5.3736
-#> 446:    93.9970   -1.9164   -4.0858    0.0114    5.9286    0.7238    2.7177    0.2164    5.3738
-#> 447:    93.9959   -1.9163   -4.0858    0.0113    5.9407    0.7237    2.7166    0.2165    5.3731
-#> 448:    93.9947   -1.9163   -4.0856    0.0113    5.9442    0.7237    2.7159    0.2167    5.3723
-#> 449:    93.9948   -1.9164   -4.0854    0.0114    5.9386    0.7234    2.7151    0.2170    5.3730
-#> 450:    93.9937   -1.9164   -4.0853    0.0115    5.9368    0.7231    2.7142    0.2172    5.3732
-#> 451:    93.9929   -1.9164   -4.0851    0.0114    5.9312    0.7229    2.7135    0.2173    5.3735
-#> 452:    93.9923   -1.9163   -4.0850    0.0112    5.9288    0.7227    2.7121    0.2175    5.3747
-#> 453:    93.9918   -1.9162   -4.0849    0.0111    5.9339    0.7225    2.7112    0.2178    5.3759
-#> 454:    93.9912   -1.9164   -4.0849    0.0111    5.9355    0.7224    2.7103    0.2181    5.3777
-#> 455:    93.9902   -1.9164   -4.0849    0.0111    5.9412    0.7223    2.7097    0.2183    5.3784
-#> 456:    93.9894   -1.9164   -4.0848    0.0110    5.9554    0.7223    2.7076    0.2186    5.3801
-#> 457:    93.9902   -1.9161   -4.0846    0.0110    5.9675    0.7219    2.7054    0.2188    5.3807
-#> 458:    93.9907   -1.9159   -4.0845    0.0109    5.9710    0.7216    2.7032    0.2191    5.3815
-#> 459:    93.9926   -1.9157   -4.0844    0.0108    5.9751    0.7213    2.7011    0.2193    5.3817
-#> 460:    93.9930   -1.9155   -4.0845    0.0107    5.9788    0.7210    2.6985    0.2197    5.3818
-#> 461:    93.9933   -1.9153   -4.0845    0.0106    5.9809    0.7208    2.6959    0.2200    5.3822
-#> 462:    93.9941   -1.9153   -4.0845    0.0105    5.9904    0.7205    2.6935    0.2203    5.3820
-#> 463:    93.9945   -1.9152   -4.0844    0.0105    5.9971    0.7201    2.6913    0.2206    5.3817
-#> 464:    93.9942   -1.9151   -4.0844    0.0104    6.0010    0.7198    2.6892    0.2209    5.3818
-#> 465:    93.9931   -1.9152   -4.0843    0.0103    6.0113    0.7193    2.6872    0.2212    5.3823
-#> 466:    93.9937   -1.9152   -4.0840    0.0101    6.0145    0.7188    2.6853    0.2215    5.3828
-#> 467:    93.9939   -1.9152   -4.0838    0.0099    6.0189    0.7182    2.6835    0.2218    5.3832
-#> 468:    93.9933   -1.9153   -4.0835    0.0097    6.0247    0.7177    2.6818    0.2221    5.3830
-#> 469:    93.9933   -1.9153   -4.0832    0.0095    6.0251    0.7173    2.6801    0.2224    5.3822
-#> 470:    93.9914   -1.9153   -4.0829    0.0092    6.0332    0.7169    2.6785    0.2226    5.3823
-#> 471:    93.9894   -1.9153   -4.0826    0.0089    6.0455    0.7165    2.6769    0.2230    5.3822
-#> 472:    93.9869   -1.9152   -4.0824    0.0086    6.0454    0.7161    2.6754    0.2232    5.3836
-#> 473:    93.9852   -1.9152   -4.0822    0.0084    6.0501    0.7159    2.6740    0.2234    5.3832
-#> 474:    93.9829   -1.9152   -4.0821    0.0082    6.0579    0.7155    2.6725    0.2235    5.3831
-#> 475:    93.9826   -1.9152   -4.0819    0.0082    6.0661    0.7150    2.6711    0.2238    5.3829
-#> 476:    93.9837   -1.9152   -4.0819    0.0082    6.0774    0.7147    2.6696    0.2241    5.3824
-#> 477:    93.9852   -1.9151   -4.0819    0.0081    6.0890    0.7145    2.6681    0.2244    5.3817
-#> 478:    93.9851   -1.9151   -4.0820    0.0080    6.0957    0.7144    2.6665    0.2246    5.3827
-#> 479:    93.9857   -1.9150   -4.0820    0.0079    6.0981    0.7144    2.6651    0.2250    5.3838
-#> 480:    93.9856   -1.9151   -4.0821    0.0080    6.0944    0.7144    2.6638    0.2255    5.3854
-#> 481:    93.9864   -1.9152   -4.0823    0.0081    6.0912    0.7144    2.6624    0.2258    5.3865
-#> 482:    93.9870   -1.9153   -4.0825    0.0081    6.0954    0.7142    2.6613    0.2262    5.3864
-#> 483:    93.9888   -1.9153   -4.0826    0.0081    6.0888    0.7141    2.6602    0.2267    5.3870
-#> 484:    93.9903   -1.9154   -4.0828    0.0082    6.0848    0.7139    2.6592    0.2272    5.3861
-#> 485:    93.9914   -1.9154   -4.0831    0.0085    6.0851    0.7138    2.6586    0.2275    5.3858
-#> 486:    93.9909   -1.9154   -4.0834    0.0088    6.0824    0.7137    2.6581    0.2278    5.3850
-#> 487:    93.9899   -1.9155   -4.0838    0.0091    6.0870    0.7137    2.6577    0.2281    5.3838
-#> 488:    93.9882   -1.9156   -4.0842    0.0095    6.0877    0.7135    2.6574    0.2284    5.3835
-#> 489:    93.9865   -1.9163   -4.0841    0.0099    6.0839    0.7139    2.6581    0.2287    5.3835
-#> 490:    93.9859   -1.9170   -4.0841    0.0104    6.0783    0.7143    2.6587    0.2290    5.3830
-#> 491:    93.9847   -1.9177   -4.0838    0.0108    6.0773    0.7148    2.6596    0.2293    5.3824
-#> 492:    93.9840   -1.9183   -4.0836    0.0110    6.0833    0.7152    2.6606    0.2295    5.3817
-#> 493:    93.9832   -1.9188   -4.0834    0.0113    6.0832    0.7157    2.6613    0.2297    5.3814
-#> 494:    93.9824   -1.9195   -4.0832    0.0115    6.0859    0.7163    2.6620    0.2299    5.3819
-#> 495:    93.9813   -1.9200   -4.0830    0.0117    6.0878    0.7169    2.6633    0.2300    5.3820
-#> 496:    93.9798   -1.9206   -4.0827    0.0118    6.0871    0.7173    2.6644    0.2302    5.3825
-#> 497:    93.9787   -1.9213   -4.0824    0.0120    6.0856    0.7178    2.6653    0.2304    5.3834
-#> 498:    93.9771   -1.9220   -4.0822    0.0123    6.0759    0.7181    2.6660    0.2308    5.3850
-#> 499:    93.9744   -1.9225   -4.0819    0.0125    6.0692    0.7183    2.6666    0.2311    5.3868
-#> 500:    93.9728   -1.9229   -4.0816    0.0129    6.0609    0.7184    2.6675    0.2314    5.3884
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |    log_k1 |    log_k2 |  g_qlogis |
-#> |.....................|     sigma |        o1 |        o2 |        o3 |
-#> |.....................|        o4 |...........|...........|...........|
-#> |    1|     319.20504 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     319.20504 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     319.20504 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    G|    Gill Diff. |     17.25 |  -0.06517 |   -0.2231 |   0.05323 |
-#> |.....................|    -31.06 |     10.54 |    -5.521 |     3.149 |
-#> |.....................|    -10.19 |...........|...........|...........|
-#> |    2|     930.59637 |    0.5572 |   -0.9500 |   -0.9943 |   -0.9135 |
-#> |.....................|  -0.07749 |    -1.170 |   -0.7520 |   -0.9767 |
-#> |.....................|   -0.6292 |...........|...........|...........|
-#> |    U|     930.59637 |     52.42 |    -1.832 |    -4.205 |    0.1099 |
-#> |.....................|     2.723 |    0.5378 |     1.159 |    0.8352 |
-#> |.....................|     1.457 |...........|...........|...........|
-#> |    X|     930.59637 |     52.42 |    0.1600 |   0.01492 |    0.5274 |
-#> |.....................|     2.723 |    0.5378 |     1.159 |    0.8352 |
-#> |.....................|     1.457 |...........|...........|...........|
-#> |    3|     366.81009 |    0.9557 |   -0.9515 |   -0.9994 |   -0.9122 |
-#> |.....................|   -0.7950 |   -0.9264 |   -0.8795 |   -0.9039 |
-#> |.....................|   -0.8647 |...........|...........|...........|
-#> |    U|     366.81009 |     89.92 |    -1.834 |    -4.210 |    0.1100 |
-#> |.....................|     2.024 |    0.7174 |     1.030 |    0.9013 |
-#> |.....................|     1.185 |...........|...........|...........|
-#> |    X|     366.81009 |     89.92 |    0.1598 |   0.01484 |    0.5275 |
-#> |.....................|     2.024 |    0.7174 |     1.030 |    0.9013 |
-#> |.....................|     1.185 |...........|...........|...........|
-#> |    4|     354.05577 |    0.9956 |   -0.9516 |   -0.9999 |   -0.9121 |
-#> |.....................|   -0.8667 |   -0.9020 |   -0.8922 |   -0.8966 |
-#> |.....................|   -0.8882 |...........|...........|...........|
-#> |    U|     354.05577 |     93.67 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.954 |    0.7353 |     1.017 |    0.9079 |
-#> |.....................|     1.158 |...........|...........|...........|
-#> |    X|     354.05577 |     93.67 |    0.1597 |   0.01484 |    0.5275 |
-#> |.....................|     1.954 |    0.7353 |     1.017 |    0.9079 |
-#> |.....................|     1.158 |...........|...........|...........|
-#> |    5|     354.18966 |    0.9996 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8739 |   -0.8996 |   -0.8935 |   -0.8959 |
-#> |.....................|   -0.8906 |...........|...........|...........|
-#> |    U|     354.18966 |     94.04 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7371 |     1.015 |    0.9086 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.18966 |     94.04 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7371 |     1.015 |    0.9086 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    6|     354.21855 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8746 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.21855 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.21855 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    7|     354.22159 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22159 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22159 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    8|     354.22201 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22201 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22201 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    9|     354.22204 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22204 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22204 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   10|     354.22204 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22204 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22204 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   11|     354.22204 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22204 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22204 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   12|     354.22204 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22204 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22204 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   13|     354.22204 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22204 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22204 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   14|     354.22204 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|     354.22204 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|     354.22204 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   15|     354.22200 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|       354.222 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|       354.222 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   16|     354.22200 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|       354.222 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|       354.222 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |   17|     354.22200 |     1.000 |   -0.9516 |    -1.000 |   -0.9121 |
-#> |.....................|   -0.8747 |   -0.8993 |   -0.8937 |   -0.8958 |
-#> |.....................|   -0.8908 |...........|...........|...........|
-#> |    U|       354.222 |     94.08 |    -1.834 |    -4.211 |    0.1100 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> |    X|       354.222 |     94.08 |    0.1597 |   0.01483 |    0.5275 |
-#> |.....................|     1.947 |    0.7373 |     1.015 |    0.9087 |
-#> |.....................|     1.155 |...........|...........|...........|
-#> calculating covariance matrix
+f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem",
+  control = saemControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei",
+  control = foceiControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> calculating covariance matrix
 #> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo

-f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> 1:    93.5894   -2.4029   -3.9815    2.0318    3.0448    0.8581    1.0844    0.3182   21.0327
-#> 2:    93.5363   -2.3652   -3.9374    1.9473    2.8925    0.8152    1.0302    0.3023   14.7642
-#> 3:    93.3061   -2.3950   -3.8630    1.9537    2.7479    0.7744    1.0729    0.2872   12.2332
-#> 4:    93.4757   -2.3967   -3.8509    1.9504    2.6105    0.7357    1.1580    0.2729   11.6140
-#> 5:    93.6045   -2.3957   -3.8593    1.9732    2.4800    0.6989    1.1001    0.2592   11.0776
-#> 6:    93.6138   -2.4089   -3.9577    1.9557    2.8119    0.6640    1.0451    0.2463   11.5001
-#> 7:    93.4125   -2.3879   -3.8924    1.9950    3.1015    0.6308    1.0649    0.2339   10.6133
-#> 8:    93.5798   -2.3850   -3.9314    1.9888    3.0019    0.5992    1.0116    0.2222   10.4278
-#> 9:    93.1493   -2.3918   -3.9011    2.0040    4.3802    0.5693    1.0723    0.2111   10.2172
-#> 10:    93.5411   -2.3906   -3.8778    1.9664    4.5606    0.5408    1.0616    0.2006   10.1244
-#> 11:    93.3749   -2.4011   -3.8586    1.9682    4.3326    0.5138    1.0696    0.1905   10.1145
-#> 12:    93.0136   -2.3943   -3.8530    1.9633    4.1160    0.4881    1.0606    0.1810   10.0091
-#> 13:    93.1809   -2.4059   -3.9088    1.9821    3.9102    0.5448    1.0076    0.1720    9.8058
-#> 14:    93.3891   -2.4107   -3.9285    1.9894    3.7147    0.5504    0.9810    0.1634   10.2784
-#> 15:    93.4041   -2.4114   -3.9711    2.0216    4.4250    0.6070    0.9495    0.1552    9.4036
-#> 16:    93.4244   -2.4191   -4.0366    2.0511    4.2037    0.6035    0.9020    0.1474   10.0835
-#> 17:    93.6295   -2.4103   -4.0143    2.0509    4.0926    0.5997    0.8599    0.1401    9.7686
-#> 18:    93.6653   -2.4165   -3.9724    2.0405    3.8880    0.5979    0.9046    0.1331    9.6299
-#> 19:    93.6510   -2.4088   -3.9969    2.0328    3.6936    0.5934    0.9181    0.1264    9.3236
-#> 20:    93.6048   -2.4117   -3.9552    2.0268    3.9084    0.5879    1.0078    0.1201    9.6618
-#> 21:    94.0961   -2.4193   -3.9812    2.0552    3.7456    0.5743    0.9574    0.1141    9.6510
-#> 22:    93.9157   -2.4202   -3.9102    2.0263    5.0447    0.6198    0.9742    0.1294    9.6463
-#> 23:    94.1580   -2.4286   -3.9223    2.0441    4.7925    0.5981    0.9312    0.1230    9.8346
-#> 24:    94.4405   -2.4141   -3.9564    2.0383    4.5529    0.5925    0.9173    0.1168   10.6161
-#> 25:    93.8846   -2.3958   -4.0122    2.0053    4.9956    0.5677    0.8715    0.1173   10.3823
-#> 26:    93.6815   -2.3835   -3.9801    1.9872    5.6625    0.5514    0.8368    0.1114    9.8283
-#> 27:    93.6463   -2.3779   -3.9731    1.9833    5.3794    0.5566    0.8650    0.1059    9.5439
-#> 28:    93.7974   -2.3980   -3.9583    1.9657    6.4804    0.5366    0.8756    0.1006    9.7998
-#> 29:    93.6921   -2.4221   -3.8982    1.9701    6.1564    0.6070    0.9713    0.0955    9.2988
-#> 30:    93.3112   -2.4200   -3.8916    1.9702    6.6968    0.6110    0.9538    0.0908    9.1812
-#> 31:    93.9900   -2.4282   -3.9448    2.0257    6.3620    0.6071    0.9061    0.0862    9.4865
-#> 32:    93.8014   -2.4241   -3.9364    2.0053    6.8497    0.6173    0.8608    0.0819    9.5589
-#> 33:    94.0330   -2.4215   -3.9888    2.0034    6.5072    0.6142    0.8178    0.0778   10.2023
-#> 34:    93.5811   -2.4215   -3.9917    2.0170    6.1819    0.5907    0.8314    0.0842   10.2204
-#> 35:    93.9308   -2.4210   -3.8798    2.0046    6.7593    0.5877    1.1132    0.0800    9.2384
-#> 36:    94.0000   -2.4325   -3.8970    2.0457    6.4213    0.5886    1.0731    0.0835    8.8987
-#> 37:    93.4010   -2.4325   -3.9306    2.0550    7.2268    0.5886    1.0220    0.0969    9.1261
-#> 38:    93.3896   -2.4291   -3.9250    2.0148    6.8655    0.5885    0.9709    0.1039    9.2989
-#> 39:    93.3821   -2.4349   -3.9148    2.0368    6.5222    0.6059    0.9647    0.1095    9.2864
-#> 40:    93.1382   -2.4685   -3.9384    2.1083    8.6249    0.6287    1.0265    0.1066    9.6411
-#> 41:    92.7963   -2.4643   -3.8992    2.0585    8.1937    0.6376    1.1117    0.1234    9.4738
-#> 42:    92.7160   -2.4545   -3.9652    2.0680    7.7840    0.6068    1.0561    0.1173    9.4776
-#> 43:    93.0070   -2.4360   -4.0223    2.0624    7.9556    0.5840    1.0033    0.1114    9.7197
-#> 44:    93.3836   -2.4207   -4.0739    2.0872    7.5578    0.5788    0.9531    0.1058   10.3515
-#> 45:    93.3240   -2.4382   -4.0210    2.1103    7.1799    0.6211    0.9055    0.1165   10.5050
-#> 46:    93.1921   -2.4438   -4.0330    2.0842    7.3884    0.6159    0.8602    0.1107   10.7251
-#> 47:    92.9710   -2.4351   -4.0155    2.1117    7.0189    0.5998    0.8519    0.1091   10.2972
-#> 48:    93.0129   -2.4395   -3.9677    2.0986    6.6680    0.5804    0.8775    0.1058   10.8515
-#> 49:    92.6562   -2.4474   -4.0295    2.0877    6.3346    0.6338    0.8723    0.1155   10.0641
-#> 50:    92.5101   -2.4612   -4.0295    2.0845    6.0179    0.6197    0.8742    0.1097    9.9048
-#> 51:    92.9446   -2.4615   -3.9927    2.1199    5.7170    0.6165    0.9311    0.1042    9.8383
-#> 52:    92.8362   -2.4525   -3.9682    2.0787    5.4311    0.6329    0.9647    0.0990    9.0726
-#> 53:    92.8579   -2.4598   -3.9324    2.0529    5.1596    0.6057    0.9192    0.0940    9.5677
-#> 54:    92.8667   -2.4858   -3.9104    2.0454    5.0661    0.6304    1.0025    0.0893    9.0977
-#> 55:    93.2327   -2.4650   -3.8323    2.0628    6.8188    0.6499    1.1366    0.0852    8.5677
-#> 56:    92.9319   -2.4794   -3.8376    2.0490    6.4778    0.6635    1.1141    0.1064    9.0723
-#> 57:    93.1126   -2.5128   -3.8223    2.0834    6.1539    0.6637    1.1361    0.1010    9.2678
-#> 58:    93.5085   -2.4894   -3.8723    2.0650    5.8462    0.6745    1.0793    0.0960    9.0367
-#> 59:    93.7882   -2.4614   -3.9241    2.0707    5.5539    0.6898    1.0254    0.0912    8.7466
-#> 60:    94.1492   -2.4386   -3.9415    2.0599    5.2762    0.6711    0.9741    0.0932    8.4466
-#> 61:    94.4215   -2.4272   -3.9647    2.0482    5.0124    0.6549    0.9254    0.0911    8.7870
-#> 62:    94.3607   -2.4053   -3.9633    1.9966    4.7618    0.6534    0.8878    0.1221    9.0404
-#> 63:    94.3958   -2.4179   -3.9386    2.0041    4.5237    0.6462    0.9360    0.1245    9.0491
-#> 64:    94.5204   -2.4175   -3.9411    2.0106    4.2975    0.6532    0.9657    0.1183    8.9115
-#> 65:    94.5674   -2.4117   -3.9701    2.0546    4.0826    0.6438    0.9238    0.1247    8.7293
-#> 66:    94.2199   -2.4337   -3.9298    2.0287    4.7686    0.6582    0.9262    0.1185    9.0519
-#> 67:    94.2756   -2.4305   -3.9706    2.0782    4.5301    0.6512    0.8799    0.1126    9.1397
-#> 68:    94.4195   -2.4193   -4.0049    2.0643    4.3036    0.6804    0.8359    0.1220    9.5306
-#> 69:    94.5255   -2.4183   -4.0119    2.0733    4.0884    0.6784    0.8577    0.1297    9.4535
-#> 70:    94.5668   -2.4117   -3.9662    2.0762    4.2149    0.6511    0.9325    0.1475    9.1637
-#> 71:    94.7464   -2.4147   -3.9937    2.0942    4.2418    0.6571    0.9524    0.1540    9.6576
-#> 72:    94.4869   -2.4160   -4.0050    2.1075    4.8520    0.6687    1.0119    0.1488    9.4234
-#> 73:    94.3747   -2.4423   -4.0072    2.1484    6.4364    0.6948    1.0011    0.1438    9.1490
-#> 74:    94.3997   -2.4464   -4.0147    2.1965    6.1146    0.7030    1.0566    0.1521    9.0697
-#> 75:    94.4187   -2.4566   -3.9611    2.1337    5.8089    0.6866    1.1666    0.1656    8.9436
-#> 76:    94.4381   -2.4502   -3.9816    2.1209    5.6488    0.7266    1.1449    0.1573    8.9289
-#> 77:    94.6421   -2.4446   -3.9603    2.1544    5.3663    0.6968    1.2087    0.1662    8.5186
-#> 78:    94.8397   -2.4420   -3.9690    2.1380    5.0980    0.6969    1.1833    0.1578    8.9071
-#> 79:    94.4296   -2.4547   -3.9576    2.1569    6.3095    0.6829    1.1850    0.1544    9.1345
-#> 80:    93.9628   -2.4530   -3.9312    2.0956    8.5844    0.6880    1.2548    0.1835    8.6936
-#> 81:    94.2900   -2.4687   -3.8570    2.0779    9.0596    0.6993    1.2012    0.1743    8.9092
-#> 82:    93.9652   -2.4742   -3.9261    2.0913    8.6066    0.6970    1.1667    0.1656    8.4359
-#> 83:    94.0828   -2.4739   -3.8603    2.0587    8.1763    0.7123    1.2575    0.1638    8.5431
-#> 84:    93.5926   -2.4645   -3.8993    2.0391    9.8721    0.7178    1.1947    0.1556    8.5623
-#> 85:    93.7052   -2.4692   -3.8411    2.0448    9.3785    0.7251    1.1349    0.1478    8.5558
-#> 86:    93.8043   -2.4726   -3.9028    2.0745    8.9096    0.7064    1.0782    0.1404    9.1308
-#> 87:    93.5704   -2.4836   -3.8694    2.0999   12.3224    0.7284    1.0922    0.1334    8.8645
-#> 88:    93.5715   -2.4827   -3.9202    2.0861   11.7063    0.7541    1.0376    0.1267    9.2433
-#> 89:    93.6894   -2.4720   -3.8964    2.1093   12.4610    0.7727    1.0218    0.1325    9.0321
-#> 90:    93.2881   -2.4787   -3.9464    2.1137   11.8380    0.7850    0.9707    0.1258    8.8265
-#> 91:    93.8454   -2.4626   -3.9566    2.1181   11.2461    0.7620    0.9579    0.1396    8.8279
-#> 92:    93.8268   -2.4639   -3.8951    2.0936   10.6838    0.7618    1.1083    0.1553    8.4609
-#> 93:    94.0622   -2.4853   -3.8531    2.0740   10.1496    0.7493    1.1237    0.1596    8.2057
-#> 94:    93.6190   -2.4843   -3.8857    2.0625    9.6421    0.7596    1.1104    0.1686    8.3522
-#> 95:    93.6352   -2.4725   -3.9243    2.0582    9.1600    0.7732    1.0549    0.1694    8.3993
-#> 96:    93.5291   -2.4707   -3.9318    2.0612    8.7020    0.7853    1.0639    0.1609    8.2908
-#> 97:    93.0626   -2.4639   -3.9255    2.0887    8.4092    0.7717    1.1477    0.1685    8.2710
-#> 98:    93.3712   -2.4677   -3.9642    2.1350    7.9888    0.7703    1.0903    0.1921    8.5468
-#> 99:    93.7108   -2.4848   -3.9775    2.1733    7.5893    0.7490    1.0367    0.1825    8.5629
-#> 100:    94.1114   -2.4867   -4.0111    2.1705    7.2099    0.7446    0.9849    0.1832    8.6964
-#> 101:    93.7547   -2.4897   -3.9793    2.1817    7.1755    0.7513    0.9899    0.1774    8.5077
-#> 102:    93.8818   -2.5029   -3.9929    2.2028    6.8167    0.7137    1.0045    0.1685    8.3706
-#> 103:    94.0026   -2.5094   -3.9680    2.2059    6.4759    0.7073    1.0498    0.1601    8.3087
-#> 104:    93.5946   -2.5260   -3.9640    2.2209    6.2674    0.7688    1.0548    0.1531    8.3444
-#> 105:    93.3863   -2.5431   -4.0087    2.2211    7.1040    0.7987    1.0020    0.1454    8.2210
-#> 106:    93.1536   -2.5365   -4.0243    2.2457    6.7488    0.7909    0.9519    0.1389    8.0950
-#> 107:    93.2220   -2.5446   -4.0016    2.2508    6.4114    0.8108    0.9483    0.1364    8.5629
-#> 108:    93.0778   -2.5470   -3.9678    2.2329    6.4774    0.8077    1.0081    0.1850    9.2740
-#> 109:    93.8925   -2.5453   -3.9560    2.2193    6.1535    0.8079    1.0608    0.2111    9.2651
-#> 110:    94.3171   -2.5179   -4.0040    2.2145    5.8458    0.7874    1.0520    0.2135    8.9788
-#> 111:    94.0655   -2.5069   -3.9752    2.2009    5.5536    0.8056    1.1206    0.2192    8.9410
-#> 112:    93.8552   -2.4994   -3.9791    2.1597    5.2759    0.8012    1.0646    0.2365    8.9570
-#> 113:    93.5190   -2.5053   -3.9760    2.1727    5.0121    0.8326    1.0114    0.2246    9.2154
-#> 114:    93.5531   -2.5083   -3.9569    2.1636    4.7615    0.8255    0.9879    0.2134    9.1197
-#> 115:    93.4780   -2.5217   -3.9467    2.1529    4.5234    0.8314    1.0392    0.2027    8.7850
-#> 116:    93.5707   -2.5216   -3.9098    2.1667    4.2972    0.8261    1.1213    0.1926    9.2991
-#> 117:    93.6610   -2.5445   -3.8775    2.1473    4.0824    0.8122    1.1232    0.1830    9.2054
-#> 118:    93.4315   -2.5251   -3.9166    2.1365    4.6012    0.7933    1.0690    0.1738    8.8061
-#> 119:    93.2491   -2.5265   -3.9236    2.1671    5.0672    0.8046    1.0711    0.1709    8.2293
-#> 120:    93.2605   -2.5327   -3.9714    2.1984    4.8138    0.8025    1.0176    0.1623    7.9088
-#> 121:    93.5831   -2.5448   -3.9669    2.2195    4.5731    0.8079    0.9921    0.1542    8.2211
-#> 122:    93.3408   -2.5460   -3.9710    2.2235    4.6838    0.8053    1.0377    0.1658    8.2934
-#> 123:    93.4581   -2.5395   -3.9487    2.2279    4.4496    0.8298    1.0338    0.1732    8.2859
-#> 124:    93.0562   -2.5565   -3.9587    2.2299    4.2272    0.8590    1.0531    0.1964    8.1244
-#> 125:    93.0576   -2.5660   -3.9434    2.2457    4.0158    0.8564    1.0768    0.1866    8.3730
-#> 126:    92.8366   -2.5571   -3.9463    2.2096    3.8150    0.8551    1.0476    0.1773    8.3820
-#> 127:    92.9607   -2.5595   -3.9773    2.2325    3.6243    0.8497    0.9952    0.1684    9.2276
-#> 128:    93.0655   -2.5463   -3.9731    2.1901    3.4430    0.8903    0.9454    0.1600    8.8096
-#> 129:    93.0669   -2.5467   -3.9713    2.2204    3.2709    0.8905    0.9234    0.1520    8.8686
-#> 130:    93.2036   -2.5524   -3.9702    2.2070    3.1073    0.8719    0.9514    0.1578    8.8433
-#> 131:    93.3565   -2.5544   -3.9809    2.1654    2.9520    0.8777    0.9117    0.1764    8.9770
-#> 132:    93.0371   -2.5364   -3.9250    2.1761    2.8044    0.8338    1.0518    0.1731    8.5405
-#> 133:    93.5727   -2.5388   -3.8759    2.1580    3.6769    0.8616    1.0981    0.1858    8.5303
-#> 134:    93.4962   -2.5341   -3.9006    2.1394    4.3695    0.8904    1.0432    0.1765    8.7067
-#> 135:    93.3219   -2.5413   -3.8922    2.1888    4.1510    0.8971    1.0435    0.1857    8.4977
-#> 136:    93.3582   -2.5477   -3.8412    2.1957    3.9435    0.8816    1.1954    0.2102    8.1330
-#> 137:    93.2791   -2.5313   -3.8936    2.1570    3.7463    0.8875    1.1356    0.1997    8.3094
-#> 138:    93.0890   -2.5428   -3.8910    2.1414    3.5590    0.8826    1.1008    0.2120    8.2653
-#> 139:    93.2404   -2.5407   -3.8926    2.1727    3.3810    0.8829    1.1068    0.2014    8.3739
-#> 140:    93.0870   -2.5514   -3.9131    2.2182    3.2120    0.8712    1.0870    0.1914    8.6179
-#> 141:    93.2715   -2.5499   -3.9460    2.2216    3.4383    0.8470    1.0662    0.1900    8.4034
-#> 142:    93.1915   -2.5583   -3.9990    2.2475    5.2653    0.8607    1.0129    0.2061    7.9891
-#> 143:    93.3709   -2.5650   -3.9422    2.2369    5.0020    0.8748    1.2043    0.2248    8.0084
-#> 144:    93.2092   -2.5706   -3.9016    2.1930    4.7519    0.8667    1.1977    0.2179    8.2733
-#> 145:    92.6640   -2.5733   -3.9225    2.1859    4.5143    0.8636    1.1695    0.2070    8.6212
-#> 146:    92.7581   -2.5695   -3.9055    2.1801    5.4209    0.8589    1.1678    0.1967    8.9378
-#> 147:    93.1089   -2.5707   -3.9825    2.2113    7.6640    0.8710    1.1094    0.1934    9.0543
-#> 148:    93.0803   -2.5672   -3.9461    2.2066    9.9043    0.8648    1.1043    0.1863    8.6209
-#> 149:    92.6332   -2.5468   -3.9425    2.1881    9.4091    0.8278    1.1313    0.1769    8.4652
-#> 150:    92.9068   -2.5440   -3.9531    2.2005    8.9386    0.8189    1.1104    0.1681    8.4196
-#> 151:    92.7324   -2.5497   -3.9648    2.2387    8.4917    0.8205    1.1421    0.1597    8.4228
-#> 152:    93.0394   -2.5282   -3.9916    2.2251    3.9029    0.8190    1.0320    0.1612    8.3453
-#> 153:    93.3137   -2.5268   -3.9993    2.2294    3.7951    0.8187    1.0311    0.1780    8.4258
-#> 154:    93.6677   -2.5264   -3.9756    2.2615    4.8704    0.8177    1.1355    0.1799    8.7204
-#> 155:    94.0822   -2.5409   -4.0456    2.2507    5.1202    0.8032    0.9930    0.1613    8.8844
-#> 156:    93.6289   -2.5388   -4.1150    2.2777    4.6367    0.8080    0.8336    0.1817    8.4370
-#> 157:    93.9171   -2.5327   -4.0218    2.2696    3.1121    0.8069    1.0394    0.1800    8.5006
-#> 158:    94.0010   -2.5357   -4.0036    2.2695    3.1485    0.8087    1.1132    0.2048    8.7160
-#> 159:    94.1277   -2.5541   -3.9717    2.2773    5.1432    0.8088    1.0732    0.1980    8.5378
-#> 160:    94.0075   -2.5436   -3.9550    2.2796    4.7826    0.8286    1.0820    0.1953    8.3885
-#> 161:    93.6793   -2.5471   -3.9675    2.2713    3.9366    0.8603    1.0682    0.1972    8.3026
-#> 162:    93.2649   -2.5429   -3.9564    2.2406    2.7349    0.8469    1.0889    0.1929    8.3765
-#> 163:    93.2072   -2.5519   -3.9786    2.2535    3.1500    0.8361    1.1240    0.1997    8.4527
-#> 164:    93.4059   -2.5471   -4.0398    2.2257    2.8708    0.8284    1.0541    0.2105    8.4984
-#> 165:    93.2579   -2.5407   -3.9665    2.2305    2.7397    0.8251    1.1355    0.2302    7.9794
-#> 166:    93.4900   -2.5465   -3.9565    2.2316    1.9775    0.8359    1.0939    0.2243    8.1279
-#> 167:    93.3825   -2.5567   -3.9784    2.2276    2.3737    0.8251    1.0894    0.2254    8.6657
-#> 168:    93.2568   -2.5681   -3.9993    2.2818    2.6721    0.8237    1.1398    0.2207    8.4894
-#> 169:    93.0484   -2.5468   -3.9693    2.2586    1.9105    0.8518    1.1911    0.1917    8.5627
-#> 170:    93.2703   -2.5730   -3.9059    2.2512    2.1481    0.8068    1.3267    0.2198    8.2260
-#> 171:    93.2041   -2.5720   -3.8992    2.2227    2.7790    0.8045    1.2387    0.2059    8.1401
-#> 172:    92.7596   -2.5722   -3.8802    2.2537    2.9977    0.8049    1.2807    0.1831    8.3375
-#> 173:    92.7734   -2.5716   -3.8811    2.1987    3.0176    0.8063    1.3070    0.2285    8.5061
-#> 174:    92.5561   -2.5700   -3.9236    2.2351    3.0286    0.8250    1.2000    0.2200    8.0725
-#> 175:    92.5072   -2.5724   -3.9968    2.2479    2.4287    0.8333    1.0169    0.2235    8.2600
-#> 176:    92.3531   -2.5787   -3.9977    2.2407    2.9999    0.8167    0.9813    0.2451    8.7505
-#> 177:    92.4672   -2.5746   -4.0095    2.2733    2.8040    0.8361    0.9794    0.2363    8.5176
-#> 178:    92.5747   -2.5981   -3.9921    2.2835    1.8203    0.8411    0.9795    0.2112    8.8034
-#> 179:    92.7101   -2.5766   -3.9697    2.2337    1.7808    0.8348    1.0402    0.2247    8.3952
-#> 180:    92.5348   -2.5714   -3.9595    2.2236    1.2661    0.8361    1.0107    0.2375    8.7156
-#> 181:    92.7241   -2.5730   -3.9205    2.2162    1.1047    0.8321    1.1192    0.2147    8.8821
-#> 182:    92.9177   -2.5864   -3.9351    2.2280    1.2069    0.8108    1.1022    0.2163    8.5703
-#> 183:    92.8646   -2.5704   -3.9755    2.2192    1.5680    0.8232    0.9400    0.1848    8.6586
-#> 184:    92.8081   -2.5759   -3.9981    2.2411    1.7739    0.8394    0.8711    0.1788    8.6327
-#> 185:    92.6830   -2.5700   -4.0110    2.2360    1.5375    0.8093    0.9114    0.1782    8.6703
-#> 186:    92.7691   -2.5764   -3.9671    2.2148    1.8813    0.8117    0.9794    0.1901    8.4813
-#> 187:    92.7540   -2.5659   -3.9695    2.2543    1.3755    0.8130    1.0332    0.1960    8.5371
-#> 188:    92.5722   -2.5650   -3.9527    2.2552    1.4000    0.8142    1.1013    0.1881    8.2025
-#> 189:    92.9404   -2.5644   -3.9446    2.2579    1.3589    0.8157    1.1262    0.1741    8.2347
-#> 190:    92.8142   -2.5628   -3.9397    2.2549    1.1871    0.8241    1.1571    0.1728    8.1590
-#> 191:    92.7352   -2.5682   -3.9476    2.2502    0.8302    0.7954    1.1448    0.1859    8.6148
-#> 192:    92.7380   -2.5574   -3.9273    2.2318    0.6692    0.8185    1.1124    0.1932    8.5279
-#> 193:    92.9199   -2.5652   -3.9586    2.2184    0.9877    0.8097    1.1689    0.1709    8.7071
-#> 194:    93.0042   -2.5651   -3.9699    2.2302    1.3311    0.8135    1.1202    0.1832    8.8051
-#> 195:    92.8090   -2.5890   -3.9799    2.2360    0.9251    0.8313    1.0192    0.1806    9.3110
-#> 196:    92.5114   -2.5894   -3.9883    2.2553    0.8504    0.8299    1.0665    0.1855    8.9668
-#> 197:    92.6704   -2.5845   -3.9577    2.2490    0.3567    0.8365    1.0893    0.1896    8.5856
-#> 198:    92.7249   -2.5753   -3.9775    2.2327    0.4282    0.8506    1.0736    0.2003    8.7110
-#> 199:    92.5538   -2.5696   -3.9550    2.2382    0.3177    0.8550    1.1060    0.2132    8.5431
-#> 200:    92.6352   -2.5716   -3.9921    2.2372    0.2500    0.8592    1.0083    0.2057    8.5811
-#> 201:    92.6440   -2.5663   -3.9931    2.2219    0.2611    0.8647    1.0130    0.1931    8.6428
-#> 202:    92.6090   -2.5633   -3.9837    2.2198    0.2389    0.8680    1.0373    0.1958    8.6818
-#> 203:    92.6180   -2.5627   -3.9823    2.2185    0.2315    0.8627    1.0398    0.1939    8.6310
-#> 204:    92.6140   -2.5628   -3.9783    2.2176    0.2289    0.8588    1.0462    0.1923    8.5391
-#> 205:    92.6337   -2.5619   -3.9802    2.2190    0.2227    0.8579    1.0407    0.1965    8.5514
-#> 206:    92.6373   -2.5615   -3.9835    2.2175    0.2313    0.8580    1.0330    0.2006    8.5635
-#> 207:    92.6403   -2.5594   -3.9836    2.2189    0.2365    0.8608    1.0282    0.2017    8.5721
-#> 208:    92.6415   -2.5587   -3.9862    2.2192    0.2480    0.8615    1.0221    0.2001    8.5738
-#> 209:    92.6303   -2.5586   -3.9872    2.2180    0.2544    0.8608    1.0127    0.1966    8.6159
-#> 210:    92.6278   -2.5584   -3.9829    2.2178    0.2577    0.8576    1.0149    0.1932    8.6336
-#> 211:    92.6320   -2.5580   -3.9844    2.2163    0.2614    0.8544    1.0057    0.1902    8.6594
-#> 212:    92.6266   -2.5576   -3.9802    2.2140    0.2554    0.8515    1.0125    0.1891    8.6549
-#> 213:    92.6226   -2.5570   -3.9771    2.2114    0.2491    0.8468    1.0201    0.1879    8.6612
-#> 214:    92.6217   -2.5570   -3.9759    2.2119    0.2430    0.8429    1.0289    0.1859    8.6700
-#> 215:    92.6212   -2.5573   -3.9743    2.2121    0.2354    0.8394    1.0383    0.1853    8.6796
-#> 216:    92.6151   -2.5566   -3.9736    2.2125    0.2329    0.8378    1.0446    0.1850    8.7036
-#> 217:    92.6073   -2.5558   -3.9759    2.2133    0.2311    0.8373    1.0459    0.1854    8.7185
-#> 218:    92.6090   -2.5556   -3.9771    2.2142    0.2312    0.8373    1.0499    0.1866    8.7181
-#> 219:    92.6166   -2.5553   -3.9764    2.2142    0.2358    0.8376    1.0624    0.1882    8.7228
-#> 220:    92.6268   -2.5549   -3.9770    2.2150    0.2404    0.8395    1.0671    0.1899    8.7325
-#> 221:    92.6337   -2.5548   -3.9765    2.2172    0.2460    0.8412    1.0713    0.1900    8.7409
-#> 222:    92.6383   -2.5563   -3.9796    2.2211    0.2499    0.8412    1.0667    0.1898    8.7456
-#> 223:    92.6399   -2.5575   -3.9806    2.2259    0.2494    0.8406    1.0665    0.1898    8.7564
-#> 224:    92.6424   -2.5589   -3.9840    2.2296    0.2451    0.8412    1.0624    0.1894    8.7571
-#> 225:    92.6431   -2.5599   -3.9883    2.2336    0.2427    0.8423    1.0555    0.1885    8.7754
-#> 226:    92.6393   -2.5612   -3.9919    2.2371    0.2384    0.8431    1.0488    0.1886    8.7904
-#> 227:    92.6354   -2.5630   -3.9918    2.2406    0.2361    0.8432    1.0501    0.1892    8.8070
-#> 228:    92.6328   -2.5650   -3.9926    2.2437    0.2336    0.8434    1.0524    0.1908    8.8133
-#> 229:    92.6328   -2.5672   -3.9913    2.2462    0.2318    0.8439    1.0578    0.1926    8.8314
-#> 230:    92.6322   -2.5684   -3.9911    2.2482    0.2269    0.8426    1.0621    0.1952    8.8464
-#> 231:    92.6263   -2.5698   -3.9910    2.2500    0.2240    0.8418    1.0628    0.1963    8.8734
-#> 232:    92.6228   -2.5710   -3.9908    2.2515    0.2218    0.8411    1.0644    0.1977    8.9056
-#> 233:    92.6235   -2.5721   -3.9919    2.2545    0.2192    0.8409    1.0649    0.1983    8.9192
-#> 234:    92.6232   -2.5727   -3.9927    2.2551    0.2171    0.8397    1.0649    0.1981    8.9294
-#> 235:    92.6219   -2.5733   -3.9924    2.2562    0.2155    0.8390    1.0646    0.1978    8.9242
-#> 236:    92.6212   -2.5737   -3.9924    2.2574    0.2145    0.8384    1.0639    0.1975    8.9292
-#> 237:    92.6211   -2.5738   -3.9938    2.2588    0.2142    0.8379    1.0607    0.1970    8.9400
-#> 238:    92.6194   -2.5735   -3.9931    2.2589    0.2155    0.8373    1.0630    0.1969    8.9371
-#> 239:    92.6175   -2.5734   -3.9928    2.2593    0.2155    0.8371    1.0648    0.1967    8.9315
-#> 240:    92.6175   -2.5729   -3.9923    2.2593    0.2143    0.8367    1.0673    0.1963    8.9180
-#> 241:    92.6155   -2.5728   -3.9917    2.2591    0.2133    0.8372    1.0695    0.1960    8.9139
-#> 242:    92.6135   -2.5726   -3.9923    2.2588    0.2136    0.8375    1.0681    0.1965    8.9191
-#> 243:    92.6115   -2.5726   -3.9930    2.2592    0.2127    0.8375    1.0683    0.1969    8.9117
-#> 244:    92.6106   -2.5726   -3.9925    2.2588    0.2123    0.8381    1.0704    0.1975    8.9124
-#> 245:    92.6065   -2.5730   -3.9930    2.2586    0.2127    0.8388    1.0691    0.1982    8.9140
-#> 246:    92.6046   -2.5734   -3.9931    2.2588    0.2109    0.8397    1.0701    0.1986    8.9132
-#> 247:    92.6048   -2.5737   -3.9938    2.2597    0.2081    0.8404    1.0708    0.1989    8.9224
-#> 248:    92.6029   -2.5739   -3.9932    2.2599    0.2056    0.8410    1.0718    0.1993    8.9198
-#> 249:    92.6006   -2.5743   -3.9934    2.2598    0.2052    0.8419    1.0705    0.1996    8.9244
-#> 250:    92.5984   -2.5740   -3.9930    2.2595    0.2037    0.8417    1.0709    0.1997    8.9208
-#> 251:    92.5967   -2.5739   -3.9932    2.2595    0.2018    0.8418    1.0700    0.1996    8.9143
-#> 252:    92.5943   -2.5737   -3.9920    2.2594    0.2009    0.8412    1.0734    0.1992    8.9090
-#> 253:    92.5944   -2.5736   -3.9904    2.2588    0.1997    0.8405    1.0769    0.1995    8.9035
-#> 254:    92.5941   -2.5732   -3.9896    2.2582    0.1987    0.8394    1.0788    0.1993    8.8940
-#> 255:    92.5916   -2.5728   -3.9892    2.2571    0.1983    0.8387    1.0794    0.1988    8.8894
-#> 256:    92.5889   -2.5724   -3.9880    2.2562    0.1988    0.8382    1.0813    0.1992    8.8834
-#> 257:    92.5889   -2.5719   -3.9872    2.2557    0.2003    0.8378    1.0831    0.1995    8.8806
-#> 258:    92.5889   -2.5717   -3.9866    2.2556    0.2021    0.8377    1.0858    0.1995    8.8792
-#> 259:    92.5898   -2.5715   -3.9867    2.2556    0.2033    0.8373    1.0884    0.1999    8.8785
-#> 260:    92.5924   -2.5709   -3.9868    2.2556    0.2033    0.8367    1.0891    0.2006    8.8743
-#> 261:    92.5956   -2.5703   -3.9866    2.2552    0.2045    0.8360    1.0908    0.2014    8.8635
-#> 262:    92.5985   -2.5698   -3.9859    2.2546    0.2054    0.8354    1.0940    0.2022    8.8551
-#> 263:    92.6014   -2.5694   -3.9857    2.2544    0.2067    0.8347    1.0964    0.2028    8.8479
-#> 264:    92.6041   -2.5690   -3.9858    2.2543    0.2069    0.8338    1.0977    0.2028    8.8421
-#> 265:    92.6063   -2.5687   -3.9861    2.2541    0.2079    0.8327    1.0976    0.2029    8.8394
-#> 266:    92.6087   -2.5684   -3.9867    2.2540    0.2107    0.8318    1.0968    0.2027    8.8351
-#> 267:    92.6108   -2.5682   -3.9863    2.2534    0.2118    0.8314    1.0970    0.2032    8.8283
-#> 268:    92.6130   -2.5680   -3.9860    2.2530    0.2131    0.8309    1.0970    0.2034    8.8263
-#> 269:    92.6139   -2.5678   -3.9851    2.2526    0.2155    0.8306    1.0979    0.2040    8.8240
-#> 270:    92.6144   -2.5676   -3.9851    2.2521    0.2176    0.8303    1.0972    0.2044    8.8283
-#> 271:    92.6153   -2.5675   -3.9855    2.2518    0.2190    0.8305    1.0961    0.2049    8.8310
-#> 272:    92.6163   -2.5674   -3.9859    2.2521    0.2196    0.8305    1.0965    0.2051    8.8378
-#> 273:    92.6178   -2.5672   -3.9862    2.2520    0.2198    0.8302    1.0959    0.2051    8.8421
-#> 274:    92.6193   -2.5670   -3.9870    2.2524    0.2195    0.8299    1.0955    0.2051    8.8441
-#> 275:    92.6197   -2.5669   -3.9874    2.2526    0.2194    0.8295    1.0947    0.2052    8.8477
-#> 276:    92.6215   -2.5665   -3.9875    2.2523    0.2206    0.8288    1.0956    0.2058    8.8462
-#> 277:    92.6225   -2.5660   -3.9878    2.2522    0.2231    0.8282    1.0974    0.2064    8.8450
-#> 278:    92.6237   -2.5655   -3.9883    2.2522    0.2240    0.8277    1.0988    0.2074    8.8501
-#> 279:    92.6249   -2.5651   -3.9888    2.2524    0.2244    0.8274    1.0994    0.2083    8.8504
-#> 280:    92.6259   -2.5647   -3.9891    2.2523    0.2235    0.8270    1.0992    0.2087    8.8514
-#> 281:    92.6264   -2.5643   -3.9889    2.2522    0.2225    0.8262    1.1001    0.2090    8.8559
-#> 282:    92.6270   -2.5639   -3.9889    2.2516    0.2223    0.8255    1.0997    0.2090    8.8593
-#> 283:    92.6280   -2.5633   -3.9885    2.2503    0.2214    0.8248    1.0999    0.2101    8.8586
-#> 284:    92.6281   -2.5627   -3.9883    2.2491    0.2212    0.8241    1.0993    0.2110    8.8580
-#> 285:    92.6283   -2.5621   -3.9881    2.2481    0.2213    0.8235    1.0986    0.2118    8.8590
-#> 286:    92.6288   -2.5615   -3.9886    2.2475    0.2219    0.8231    1.0973    0.2123    8.8602
-#> 287:    92.6291   -2.5611   -3.9890    2.2470    0.2217    0.8230    1.0961    0.2133    8.8577
-#> 288:    92.6292   -2.5607   -3.9893    2.2468    0.2202    0.8229    1.0960    0.2142    8.8570
-#> 289:    92.6275   -2.5602   -3.9895    2.2464    0.2192    0.8226    1.0964    0.2151    8.8554
-#> 290:    92.6262   -2.5598   -3.9892    2.2457    0.2189    0.8223    1.0977    0.2161    8.8578
-#> 291:    92.6246   -2.5596   -3.9890    2.2454    0.2183    0.8218    1.0999    0.2165    8.8596
-#> 292:    92.6223   -2.5593   -3.9892    2.2451    0.2183    0.8213    1.1003    0.2173    8.8575
-#> 293:    92.6201   -2.5590   -3.9896    2.2447    0.2193    0.8209    1.1003    0.2175    8.8569
-#> 294:    92.6169   -2.5587   -3.9902    2.2445    0.2202    0.8204    1.0998    0.2176    8.8568
-#> 295:    92.6144   -2.5584   -3.9906    2.2442    0.2217    0.8197    1.0994    0.2176    8.8565
-#> 296:    92.6126   -2.5581   -3.9913    2.2441    0.2223    0.8188    1.0983    0.2175    8.8585
-#> 297:    92.6112   -2.5576   -3.9920    2.2439    0.2235    0.8182    1.0969    0.2175    8.8600
-#> 298:    92.6108   -2.5572   -3.9921    2.2433    0.2250    0.8174    1.0964    0.2177    8.8612
-#> 299:    92.6101   -2.5567   -3.9919    2.2425    0.2254    0.8169    1.0960    0.2178    8.8626
-#> 300:    92.6097   -2.5562   -3.9913    2.2415    0.2257    0.8163    1.0974    0.2182    8.8632
-#> 301:    92.6102   -2.5556   -3.9913    2.2407    0.2255    0.8156    1.0972    0.2183    8.8600
-#> 302:    92.6102   -2.5551   -3.9916    2.2400    0.2252    0.8156    1.0966    0.2186    8.8586
-#> 303:    92.6099   -2.5546   -3.9915    2.2391    0.2250    0.8152    1.0978    0.2189    8.8589
-#> 304:    92.6096   -2.5541   -3.9913    2.2387    0.2242    0.8149    1.0987    0.2194    8.8570
-#> 305:    92.6100   -2.5538   -3.9914    2.2383    0.2247    0.8144    1.0995    0.2202    8.8553
-#> 306:    92.6109   -2.5533   -3.9915    2.2378    0.2255    0.8144    1.1001    0.2212    8.8531
-#> 307:    92.6119   -2.5529   -3.9913    2.2371    0.2252    0.8143    1.1007    0.2217    8.8498
-#> 308:    92.6128   -2.5525   -3.9912    2.2366    0.2249    0.8142    1.1012    0.2219    8.8490
-#> 309:    92.6143   -2.5519   -3.9905    2.2357    0.2251    0.8138    1.1018    0.2224    8.8449
-#> 310:    92.6160   -2.5513   -3.9900    2.2346    0.2255    0.8136    1.1020    0.2230    8.8403
-#> 311:    92.6177   -2.5506   -3.9891    2.2333    0.2258    0.8132    1.1031    0.2236    8.8392
-#> 312:    92.6190   -2.5499   -3.9881    2.2319    0.2267    0.8130    1.1047    0.2242    8.8382
-#> 313:    92.6192   -2.5493   -3.9872    2.2305    0.2273    0.8127    1.1057    0.2249    8.8350
-#> 314:    92.6196   -2.5490   -3.9864    2.2300    0.2279    0.8129    1.1067    0.2257    8.8315
-#> 315:    92.6197   -2.5488   -3.9858    2.2295    0.2277    0.8132    1.1072    0.2266    8.8285
-#> 316:    92.6192   -2.5485   -3.9850    2.2284    0.2276    0.8133    1.1087    0.2275    8.8278
-#> 317:    92.6190   -2.5482   -3.9840    2.2275    0.2278    0.8135    1.1105    0.2282    8.8296
-#> 318:    92.6193   -2.5480   -3.9833    2.2266    0.2274    0.8133    1.1120    0.2289    8.8313
-#> 319:    92.6200   -2.5476   -3.9827    2.2257    0.2265    0.8129    1.1133    0.2297    8.8326
-#> 320:    92.6211   -2.5472   -3.9820    2.2250    0.2260    0.8124    1.1150    0.2302    8.8359
-#> 321:    92.6226   -2.5468   -3.9816    2.2246    0.2254    0.8118    1.1158    0.2308    8.8396
-#> 322:    92.6238   -2.5464   -3.9808    2.2238    0.2249    0.8114    1.1169    0.2316    8.8424
-#> 323:    92.6248   -2.5461   -3.9805    2.2231    0.2241    0.8109    1.1173    0.2320    8.8458
-#> 324:    92.6252   -2.5458   -3.9801    2.2224    0.2233    0.8103    1.1182    0.2324    8.8474
-#> 325:    92.6248   -2.5455   -3.9799    2.2216    0.2225    0.8096    1.1192    0.2328    8.8507
-#> 326:    92.6247   -2.5451   -3.9802    2.2209    0.2216    0.8091    1.1186    0.2331    8.8519
-#> 327:    92.6248   -2.5446   -3.9806    2.2203    0.2203    0.8088    1.1179    0.2335    8.8535
-#> 328:    92.6242   -2.5442   -3.9808    2.2198    0.2196    0.8084    1.1175    0.2339    8.8533
-#> 329:    92.6234   -2.5437   -3.9809    2.2192    0.2188    0.8081    1.1176    0.2342    8.8550
-#> 330:    92.6229   -2.5433   -3.9806    2.2187    0.2182    0.8078    1.1187    0.2346    8.8574
-#> 331:    92.6220   -2.5429   -3.9801    2.2181    0.2183    0.8075    1.1210    0.2352    8.8599
-#> 332:    92.6214   -2.5425   -3.9796    2.2175    0.2185    0.8072    1.1235    0.2360    8.8612
-#> 333:    92.6215   -2.5421   -3.9794    2.2170    0.2184    0.8068    1.1248    0.2365    8.8660
-#> 334:    92.6218   -2.5417   -3.9795    2.2168    0.2180    0.8065    1.1257    0.2369    8.8675
-#> 335:    92.6220   -2.5413   -3.9793    2.2164    0.2177    0.8062    1.1269    0.2374    8.8683
-#> 336:    92.6228   -2.5410   -3.9792    2.2159    0.2173    0.8059    1.1275    0.2378    8.8707
-#> 337:    92.6244   -2.5405   -3.9792    2.2153    0.2175    0.8057    1.1278    0.2387    8.8734
-#> 338:    92.6266   -2.5401   -3.9792    2.2146    0.2184    0.8057    1.1283    0.2396    8.8757
-#> 339:    92.6290   -2.5398   -3.9790    2.2144    0.2191    0.8060    1.1294    0.2403    8.8770
-#> 340:    92.6309   -2.5396   -3.9790    2.2142    0.2200    0.8061    1.1295    0.2405    8.8766
-#> 341:    92.6328   -2.5394   -3.9788    2.2142    0.2211    0.8061    1.1300    0.2406    8.8752
-#> 342:    92.6347   -2.5392   -3.9788    2.2140    0.2223    0.8062    1.1291    0.2405    8.8744
-#> 343:    92.6365   -2.5390   -3.9787    2.2139    0.2233    0.8063    1.1288    0.2405    8.8732
-#> 344:    92.6383   -2.5388   -3.9785    2.2136    0.2242    0.8060    1.1295    0.2404    8.8730
-#> 345:    92.6392   -2.5386   -3.9781    2.2133    0.2248    0.8055    1.1303    0.2401    8.8737
-#> 346:    92.6401   -2.5384   -3.9780    2.2129    0.2249    0.8051    1.1302    0.2399    8.8739
-#> 347:    92.6411   -2.5381   -3.9777    2.2124    0.2248    0.8049    1.1302    0.2399    8.8794
-#> 348:    92.6427   -2.5380   -3.9777    2.2122    0.2251    0.8047    1.1306    0.2398    8.8814
-#> 349:    92.6444   -2.5378   -3.9777    2.2119    0.2252    0.8047    1.1304    0.2397    8.8834
-#> 350:    92.6462   -2.5376   -3.9776    2.2115    0.2260    0.8043    1.1300    0.2395    8.8859
-#> 351:    92.6470   -2.5375   -3.9772    2.2110    0.2265    0.8041    1.1303    0.2392    8.8883
-#> 352:    92.6478   -2.5373   -3.9772    2.2106    0.2266    0.8037    1.1293    0.2386    8.8926
-#> 353:    92.6493   -2.5373   -3.9772    2.2103    0.2268    0.8032    1.1285    0.2381    8.8928
-#> 354:    92.6504   -2.5372   -3.9772    2.2100    0.2264    0.8028    1.1274    0.2376    8.8946
-#> 355:    92.6512   -2.5370   -3.9771    2.2096    0.2267    0.8023    1.1273    0.2373    8.8951
-#> 356:    92.6522   -2.5367   -3.9767    2.2089    0.2275    0.8018    1.1272    0.2370    8.8947
-#> 357:    92.6534   -2.5364   -3.9765    2.2080    0.2290    0.8015    1.1268    0.2369    8.8932
-#> 358:    92.6545   -2.5362   -3.9761    2.2072    0.2301    0.8011    1.1270    0.2368    8.8919
-#> 359:    92.6566   -2.5360   -3.9757    2.2064    0.2310    0.8008    1.1269    0.2369    8.8928
-#> 360:    92.6584   -2.5358   -3.9751    2.2059    0.2311    0.8005    1.1272    0.2368    8.8924
-#> 361:    92.6611   -2.5356   -3.9744    2.2051    0.2317    0.8004    1.1280    0.2369    8.8932
-#> 362:    92.6639   -2.5353   -3.9740    2.2043    0.2321    0.8003    1.1284    0.2370    8.8914
-#> 363:    92.6662   -2.5349   -3.9733    2.2033    0.2328    0.8001    1.1289    0.2371    8.8902
-#> 364:    92.6679   -2.5345   -3.9729    2.2025    0.2325    0.7998    1.1292    0.2372    8.8883
-#> 365:    92.6695   -2.5341   -3.9725    2.2019    0.2321    0.7994    1.1297    0.2373    8.8865
-#> 366:    92.6709   -2.5337   -3.9722    2.2011    0.2321    0.7990    1.1297    0.2373    8.8860
-#> 367:    92.6724   -2.5334   -3.9720    2.2005    0.2317    0.7987    1.1295    0.2372    8.8848
-#> 368:    92.6736   -2.5330   -3.9719    2.1999    0.2314    0.7985    1.1288    0.2371    8.8844
-#> 369:    92.6745   -2.5326   -3.9717    2.1994    0.2310    0.7982    1.1283    0.2371    8.8840
-#> 370:    92.6758   -2.5323   -3.9714    2.1990    0.2312    0.7980    1.1283    0.2370    8.8854
-#> 371:    92.6776   -2.5321   -3.9708    2.1984    0.2313    0.7977    1.1286    0.2369    8.8852
-#> 372:    92.6791   -2.5317   -3.9704    2.1978    0.2311    0.7973    1.1282    0.2367    8.8865
-#> 373:    92.6804   -2.5312   -3.9701    2.1969    0.2308    0.7969    1.1280    0.2366    8.8884
-#> 374:    92.6814   -2.5308   -3.9699    2.1962    0.2305    0.7965    1.1279    0.2364    8.8898
-#> 375:    92.6827   -2.5304   -3.9698    2.1954    0.2305    0.7961    1.1271    0.2360    8.8938
-#> 376:    92.6832   -2.5301   -3.9695    2.1947    0.2301    0.7957    1.1268    0.2359    8.8930
-#> 377:    92.6835   -2.5298   -3.9692    2.1941    0.2300    0.7953    1.1269    0.2357    8.8933
-#> 378:    92.6831   -2.5295   -3.9693    2.1935    0.2303    0.7950    1.1266    0.2357    8.8990
-#> 379:    92.6827   -2.5293   -3.9694    2.1933    0.2307    0.7948    1.1265    0.2356    8.9027
-#> 380:    92.6826   -2.5291   -3.9695    2.1931    0.2307    0.7947    1.1262    0.2356    8.9045
-#> 381:    92.6822   -2.5290   -3.9695    2.1929    0.2307    0.7945    1.1259    0.2355    8.9040
-#> 382:    92.6817   -2.5289   -3.9694    2.1925    0.2305    0.7943    1.1258    0.2357    8.9033
-#> 383:    92.6812   -2.5288   -3.9695    2.1922    0.2305    0.7942    1.1255    0.2358    8.9045
-#> 384:    92.6810   -2.5288   -3.9695    2.1920    0.2302    0.7940    1.1253    0.2360    8.9058
-#> 385:    92.6806   -2.5287   -3.9694    2.1918    0.2301    0.7938    1.1254    0.2361    8.9052
-#> 386:    92.6801   -2.5286   -3.9692    2.1914    0.2298    0.7936    1.1256    0.2362    8.9039
-#> 387:    92.6800   -2.5285   -3.9687    2.1914    0.2294    0.7934    1.1261    0.2361    8.9032
-#> 388:    92.6801   -2.5284   -3.9683    2.1913    0.2293    0.7931    1.1267    0.2360    8.9027
-#> 389:    92.6802   -2.5283   -3.9684    2.1912    0.2288    0.7928    1.1261    0.2360    8.9028
-#> 390:    92.6805   -2.5281   -3.9684    2.1910    0.2283    0.7925    1.1258    0.2360    8.9044
-#> 391:    92.6806   -2.5280   -3.9685    2.1908    0.2285    0.7921    1.1254    0.2360    8.9047
-#> 392:    92.6810   -2.5278   -3.9682    2.1907    0.2288    0.7918    1.1257    0.2360    8.9057
-#> 393:    92.6810   -2.5275   -3.9681    2.1906    0.2290    0.7916    1.1257    0.2360    8.9049
-#> 394:    92.6811   -2.5272   -3.9682    2.1904    0.2292    0.7913    1.1253    0.2360    8.9056
-#> 395:    92.6812   -2.5269   -3.9682    2.1900    0.2295    0.7911    1.1251    0.2362    8.9044
-#> 396:    92.6817   -2.5269   -3.9683    2.1901    0.2292    0.7911    1.1251    0.2361    8.9031
-#> 397:    92.6824   -2.5269   -3.9686    2.1903    0.2292    0.7911    1.1250    0.2361    8.9043
-#> 398:    92.6828   -2.5270   -3.9688    2.1907    0.2291    0.7913    1.1248    0.2359    8.9035
-#> 399:    92.6829   -2.5271   -3.9689    2.1909    0.2292    0.7916    1.1248    0.2358    8.9043
-#> 400:    92.6829   -2.5273   -3.9688    2.1909    0.2295    0.7919    1.1250    0.2356    8.9037
-#> 401:    92.6827   -2.5274   -3.9687    2.1910    0.2299    0.7922    1.1249    0.2356    8.9035
-#> 402:    92.6822   -2.5276   -3.9687    2.1911    0.2303    0.7926    1.1248    0.2355    8.9033
-#> 403:    92.6821   -2.5277   -3.9686    2.1913    0.2307    0.7929    1.1250    0.2354    8.9009
-#> 404:    92.6817   -2.5279   -3.9684    2.1914    0.2314    0.7930    1.1249    0.2352    8.9012
-#> 405:    92.6813   -2.5281   -3.9683    2.1915    0.2318    0.7930    1.1252    0.2349    8.9015
-#> 406:    92.6811   -2.5283   -3.9680    2.1916    0.2321    0.7930    1.1255    0.2345    8.9019
-#> 407:    92.6817   -2.5285   -3.9677    2.1918    0.2329    0.7930    1.1255    0.2343    8.9014
-#> 408:    92.6824   -2.5287   -3.9675    2.1919    0.2330    0.7930    1.1253    0.2341    8.9019
-#> 409:    92.6833   -2.5289   -3.9674    2.1922    0.2331    0.7931    1.1249    0.2338    8.9031
-#> 410:    92.6840   -2.5291   -3.9673    2.1924    0.2331    0.7930    1.1245    0.2335    8.9054
-#> 411:    92.6848   -2.5292   -3.9672    2.1926    0.2333    0.7929    1.1243    0.2333    8.9083
-#> 412:    92.6852   -2.5293   -3.9671    2.1928    0.2333    0.7931    1.1243    0.2333    8.9107
-#> 413:    92.6858   -2.5293   -3.9671    2.1929    0.2332    0.7932    1.1246    0.2332    8.9119
-#> 414:    92.6863   -2.5293   -3.9671    2.1928    0.2332    0.7934    1.1252    0.2333    8.9112
-#> 415:    92.6868   -2.5293   -3.9671    2.1928    0.2330    0.7935    1.1253    0.2332    8.9109
-#> 416:    92.6872   -2.5293   -3.9672    2.1928    0.2327    0.7935    1.1247    0.2330    8.9101
-#> 417:    92.6875   -2.5293   -3.9674    2.1929    0.2324    0.7934    1.1241    0.2330    8.9126
-#> 418:    92.6881   -2.5294   -3.9675    2.1929    0.2322    0.7935    1.1238    0.2332    8.9148
-#> 419:    92.6885   -2.5295   -3.9674    2.1929    0.2322    0.7936    1.1236    0.2331    8.9179
-#> 420:    92.6890   -2.5297   -3.9674    2.1929    0.2322    0.7936    1.1235    0.2331    8.9194
-#> 421:    92.6891   -2.5299   -3.9672    2.1930    0.2318    0.7937    1.1236    0.2330    8.9192
-#> 422:    92.6894   -2.5301   -3.9670    2.1930    0.2318    0.7937    1.1239    0.2329    8.9183
-#> 423:    92.6898   -2.5302   -3.9667    2.1931    0.2318    0.7937    1.1242    0.2327    8.9190
-#> 424:    92.6905   -2.5304   -3.9667    2.1931    0.2316    0.7937    1.1243    0.2326    8.9190
-#> 425:    92.6910   -2.5305   -3.9667    2.1932    0.2316    0.7936    1.1240    0.2327    8.9203
-#> 426:    92.6917   -2.5306   -3.9668    2.1935    0.2318    0.7937    1.1237    0.2326    8.9200
-#> 427:    92.6918   -2.5308   -3.9671    2.1939    0.2322    0.7938    1.1227    0.2326    8.9224
-#> 428:    92.6912   -2.5310   -3.9670    2.1941    0.2319    0.7939    1.1225    0.2325    8.9268
-#> 429:    92.6912   -2.5312   -3.9670    2.1944    0.2316    0.7939    1.1225    0.2324    8.9301
-#> 430:    92.6910   -2.5314   -3.9674    2.1948    0.2314    0.7940    1.1217    0.2322    8.9314
-#> 431:    92.6911   -2.5315   -3.9675    2.1950    0.2314    0.7942    1.1210    0.2320    8.9320
-#> 432:    92.6911   -2.5316   -3.9677    2.1953    0.2312    0.7944    1.1204    0.2320    8.9327
-#> 433:    92.6910   -2.5317   -3.9681    2.1955    0.2309    0.7946    1.1196    0.2320    8.9336
-#> 434:    92.6910   -2.5318   -3.9683    2.1957    0.2306    0.7949    1.1188    0.2320    8.9337
-#> 435:    92.6912   -2.5319   -3.9687    2.1960    0.2302    0.7951    1.1178    0.2319    8.9343
-#> 436:    92.6914   -2.5320   -3.9688    2.1961    0.2300    0.7953    1.1173    0.2319    8.9345
-#> 437:    92.6919   -2.5321   -3.9688    2.1962    0.2299    0.7955    1.1168    0.2318    8.9335
-#> 438:    92.6920   -2.5323   -3.9688    2.1964    0.2296    0.7957    1.1164    0.2318    8.9334
-#> 439:    92.6917   -2.5324   -3.9689    2.1965    0.2292    0.7959    1.1165    0.2317    8.9322
-#> 440:    92.6910   -2.5326   -3.9688    2.1969    0.2289    0.7960    1.1170    0.2316    8.9319
-#> 441:    92.6907   -2.5328   -3.9688    2.1973    0.2283    0.7961    1.1175    0.2316    8.9317
-#> 442:    92.6909   -2.5330   -3.9689    2.1976    0.2280    0.7962    1.1174    0.2315    8.9326
-#> 443:    92.6911   -2.5332   -3.9689    2.1980    0.2277    0.7963    1.1180    0.2315    8.9338
-#> 444:    92.6906   -2.5332   -3.9690    2.1981    0.2275    0.7963    1.1181    0.2315    8.9354
-#> 445:    92.6897   -2.5333   -3.9691    2.1982    0.2276    0.7962    1.1181    0.2315    8.9364
-#> 446:    92.6896   -2.5333   -3.9692    2.1982    0.2272    0.7962    1.1176    0.2314    8.9363
-#> 447:    92.6893   -2.5334   -3.9693    2.1982    0.2272    0.7961    1.1173    0.2313    8.9365
-#> 448:    92.6890   -2.5334   -3.9693    2.1982    0.2271    0.7961    1.1173    0.2313    8.9364
-#> 449:    92.6888   -2.5335   -3.9693    2.1982    0.2267    0.7961    1.1170    0.2313    8.9372
-#> 450:    92.6884   -2.5335   -3.9693    2.1982    0.2262    0.7959    1.1166    0.2312    8.9364
-#> 451:    92.6885   -2.5335   -3.9691    2.1981    0.2261    0.7958    1.1167    0.2312    8.9350
-#> 452:    92.6887   -2.5335   -3.9691    2.1980    0.2260    0.7957    1.1164    0.2311    8.9349
-#> 453:    92.6888   -2.5335   -3.9691    2.1979    0.2258    0.7957    1.1163    0.2310    8.9375
-#> 454:    92.6890   -2.5335   -3.9689    2.1977    0.2258    0.7957    1.1160    0.2308    8.9385
-#> 455:    92.6894   -2.5334   -3.9687    2.1975    0.2259    0.7956    1.1158    0.2307    8.9382
-#> 456:    92.6898   -2.5334   -3.9685    2.1974    0.2261    0.7957    1.1154    0.2306    8.9380
-#> 457:    92.6904   -2.5334   -3.9685    2.1975    0.2265    0.7956    1.1146    0.2304    8.9391
-#> 458:    92.6908   -2.5334   -3.9687    2.1975    0.2266    0.7956    1.1137    0.2303    8.9418
-#> 459:    92.6911   -2.5335   -3.9689    2.1975    0.2270    0.7956    1.1129    0.2303    8.9442
-#> 460:    92.6912   -2.5335   -3.9687    2.1976    0.2274    0.7957    1.1126    0.2301    8.9461
-#> 461:    92.6913   -2.5336   -3.9687    2.1975    0.2276    0.7958    1.1125    0.2300    8.9463
-#> 462:    92.6914   -2.5336   -3.9686    2.1974    0.2280    0.7959    1.1126    0.2299    8.9456
-#> 463:    92.6917   -2.5336   -3.9684    2.1973    0.2280    0.7960    1.1127    0.2297    8.9452
-#> 464:    92.6918   -2.5336   -3.9683    2.1970    0.2280    0.7961    1.1127    0.2295    8.9444
-#> 465:    92.6921   -2.5336   -3.9682    2.1967    0.2277    0.7962    1.1127    0.2294    8.9447
-#> 466:    92.6924   -2.5336   -3.9679    2.1967    0.2275    0.7964    1.1127    0.2291    8.9454
-#> 467:    92.6930   -2.5336   -3.9677    2.1966    0.2273    0.7967    1.1128    0.2290    8.9453
-#> 468:    92.6935   -2.5337   -3.9675    2.1966    0.2275    0.7970    1.1128    0.2289    8.9458
-#> 469:    92.6937   -2.5338   -3.9676    2.1967    0.2278    0.7972    1.1123    0.2287    8.9455
-#> 470:    92.6938   -2.5338   -3.9677    2.1967    0.2283    0.7974    1.1122    0.2285    8.9451
-#> 471:    92.6940   -2.5339   -3.9676    2.1969    0.2290    0.7976    1.1124    0.2283    8.9448
-#> 472:    92.6938   -2.5339   -3.9676    2.1972    0.2293    0.7977    1.1125    0.2281    8.9460
-#> 473:    92.6937   -2.5340   -3.9676    2.1972    0.2298    0.7978    1.1121    0.2278    8.9461
-#> 474:    92.6934   -2.5341   -3.9677    2.1974    0.2308    0.7978    1.1118    0.2276    8.9470
-#> 475:    92.6936   -2.5342   -3.9677    2.1978    0.2316    0.7979    1.1113    0.2273    8.9486
-#> 476:    92.6940   -2.5345   -3.9679    2.1983    0.2324    0.7981    1.1106    0.2271    8.9491
-#> 477:    92.6945   -2.5347   -3.9681    2.1989    0.2332    0.7983    1.1099    0.2269    8.9502
-#> 478:    92.6951   -2.5349   -3.9682    2.1992    0.2344    0.7986    1.1093    0.2267    8.9502
-#> 479:    92.6958   -2.5352   -3.9683    2.1995    0.2357    0.7987    1.1088    0.2266    8.9521
-#> 480:    92.6967   -2.5354   -3.9684    2.1998    0.2370    0.7988    1.1083    0.2265    8.9524
-#> 481:    92.6977   -2.5355   -3.9685    2.2001    0.2383    0.7990    1.1079    0.2263    8.9521
-#> 482:    92.6985   -2.5357   -3.9687    2.2004    0.2395    0.7992    1.1073    0.2262    8.9518
-#> 483:    92.6992   -2.5359   -3.9690    2.2008    0.2403    0.7995    1.1066    0.2262    8.9524
-#> 484:    92.7000   -2.5361   -3.9691    2.2010    0.2406    0.7998    1.1061    0.2260    8.9516
-#> 485:    92.7009   -2.5362   -3.9693    2.2015    0.2410    0.8001    1.1057    0.2261    8.9508
-#> 486:    92.7010   -2.5363   -3.9695    2.2019    0.2412    0.8004    1.1051    0.2261    8.9502
-#> 487:    92.7008   -2.5365   -3.9698    2.2023    0.2413    0.8009    1.1048    0.2260    8.9502
-#> 488:    92.7006   -2.5366   -3.9700    2.2026    0.2411    0.8012    1.1044    0.2260    8.9501
-#> 489:    92.7006   -2.5367   -3.9701    2.2029    0.2410    0.8015    1.1041    0.2261    8.9504
-#> 490:    92.7006   -2.5368   -3.9702    2.2031    0.2407    0.8015    1.1043    0.2260    8.9498
-#> 491:    92.7007   -2.5369   -3.9701    2.2034    0.2405    0.8016    1.1047    0.2261    8.9484
-#> 492:    92.7008   -2.5370   -3.9702    2.2035    0.2406    0.8017    1.1046    0.2261    8.9473
-#> 493:    92.7010   -2.5370   -3.9704    2.2037    0.2406    0.8018    1.1044    0.2261    8.9469
-#> 494:    92.7015   -2.5371   -3.9707    2.2038    0.2408    0.8019    1.1040    0.2261    8.9453
-#> 495:    92.7017   -2.5371   -3.9708    2.2039    0.2407    0.8021    1.1042    0.2262    8.9447
-#> 496:    92.7016   -2.5371   -3.9708    2.2039    0.2407    0.8022    1.1042    0.2262    8.9433
-#> 497:    92.7015   -2.5371   -3.9709    2.2039    0.2408    0.8023    1.1044    0.2262    8.9431
-#> 498:    92.7013   -2.5371   -3.9709    2.2040    0.2409    0.8024    1.1047    0.2262    8.9452
-#> 499:    92.7011   -2.5371   -3.9710    2.2039    0.2409    0.8023    1.1049    0.2261    8.9481
-#> 500:    92.7010   -2.5371   -3.9712    2.2040    0.2412    0.8022    1.1049    0.2260    8.9498
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |    log_k1 |    log_k2 |    log_tb |
-#> |.....................|     sigma |        o1 |        o2 |        o3 |
-#> |.....................|        o4 |...........|...........|...........|
-#> |    1|     360.27275 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     360.27275 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     360.27275 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    G|    Gill Diff. |     106.2 |    0.7918 |   0.06750 |     10.50 |
-#> |.....................|    -26.04 |     2.358 |    -5.196 |    -2.491 |
-#> |.....................|    -12.13 |...........|...........|...........|
-#> |    2|     7055.7467 |   0.04059 |   -0.9733 |    -1.001 |   -0.9739 |
-#> |.....................|   -0.6317 |   -0.9263 |   -0.8528 |   -0.8784 |
-#> |.....................|   -0.7843 |...........|...........|...........|
-#> |    U|     7055.7467 |     3.818 |    -2.236 |    -3.887 |     1.944 |
-#> |.....................|     2.941 |    0.7466 |     1.074 |    0.9892 |
-#> |.....................|     1.458 |...........|...........|...........|
-#> |    X|     7055.7467 |     3.818 |    0.1069 |   0.02050 |     6.988 |
-#> |.....................|     2.941 |    0.7466 |     1.074 |    0.9892 |
-#> |.....................|     1.458 |...........|...........|...........|
-#> |    3|     499.76989 |    0.9041 |   -0.9669 |    -1.000 |   -0.8885 |
-#> |.....................|   -0.8434 |   -0.9072 |   -0.8950 |   -0.8986 |
-#> |.....................|   -0.8828 |...........|...........|...........|
-#> |    U|     499.76989 |     85.03 |    -2.229 |    -3.887 |     2.030 |
-#> |.....................|     2.663 |    0.7612 |     1.031 |    0.9696 |
-#> |.....................|     1.329 |...........|...........|...........|
-#> |    X|     499.76989 |     85.03 |    0.1076 |   0.02051 |     7.611 |
-#> |.....................|     2.663 |    0.7612 |     1.031 |    0.9696 |
-#> |.....................|     1.329 |...........|...........|...........|
-#> |    4|     360.48011 |    0.9904 |   -0.9662 |    -1.000 |   -0.8799 |
-#> |.....................|   -0.8645 |   -0.9053 |   -0.8992 |   -0.9007 |
-#> |.....................|   -0.8927 |...........|...........|...........|
-#> |    U|     360.48011 |     93.15 |    -2.229 |    -3.887 |     2.038 |
-#> |.....................|     2.635 |    0.7627 |     1.026 |    0.9677 |
-#> |.....................|     1.316 |...........|...........|...........|
-#> |    X|     360.48011 |     93.15 |    0.1077 |   0.02051 |     7.676 |
-#> |.....................|     2.635 |    0.7627 |     1.026 |    0.9677 |
-#> |.....................|     1.316 |...........|...........|...........|
-#> |    5|     360.80998 |    0.9960 |   -0.9662 |    -1.000 |   -0.8794 |
-#> |.....................|   -0.8659 |   -0.9051 |   -0.8995 |   -0.9008 |
-#> |.....................|   -0.8933 |...........|...........|...........|
-#> |    U|     360.80998 |     93.68 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.633 |    0.7628 |     1.026 |    0.9676 |
-#> |.....................|     1.315 |...........|...........|...........|
-#> |    X|     360.80998 |     93.68 |    0.1077 |   0.02051 |     7.680 |
-#> |.....................|     2.633 |    0.7628 |     1.026 |    0.9676 |
-#> |.....................|     1.315 |...........|...........|...........|
-#> |    6|     361.20154 |    0.9991 |   -0.9661 |    -1.000 |   -0.8791 |
-#> |.....................|   -0.8667 |   -0.9051 |   -0.8996 |   -0.9009 |
-#> |.....................|   -0.8937 |...........|...........|...........|
-#> |    U|     361.20154 |     93.97 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.315 |...........|...........|...........|
-#> |    X|     361.20154 |     93.97 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.315 |...........|...........|...........|
-#> |    7|     361.33469 |    0.9999 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.33469 |     94.05 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.33469 |     94.05 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    8|     361.34878 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.34878 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.34878 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    9|     361.35091 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35091 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35091 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   10|     361.35004 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35004 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35004 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   11|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   12|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   13|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   14|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   15|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   16|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   17|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |   18|     361.35006 |     1.000 |   -0.9661 |    -1.000 |   -0.8790 |
-#> |.....................|   -0.8669 |   -0.9051 |   -0.8997 |   -0.9009 |
-#> |.....................|   -0.8938 |...........|...........|...........|
-#> |    U|     361.35006 |     94.06 |    -2.229 |    -3.887 |     2.039 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> |    X|     361.35006 |     94.06 |    0.1077 |   0.02051 |     7.683 |
-#> |.....................|     2.632 |    0.7629 |     1.026 |    0.9675 |
-#> |.....................|     1.314 |...........|...........|...........|
-#> calculating covariance matrix
+f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem",
+  control = saemControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei",
+  control = foceiControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> calculating covariance matrix
 #> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: gradient problems with initial estimate and covariance; see $scaleInfo

-f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> 1:    92.2167    0.0936    1.9256    3.3974    0.7958    0.7197   11.8539    0.0004
-#> 2:    92.5446    0.0892    2.4952    3.3516    0.8528    0.6837    4.5197    0.0001
-#> 3:    9.2720e+01   1.3849e-01   2.5917e+00   3.9204e+00   9.5883e-01   6.4953e-01   4.0268e+00   5.9554e-05
-#> 4:    92.6098    0.1052    2.5494    5.0533    1.0968    0.6171    3.2396    0.0200
-#> 5:    92.6795    0.0406    2.4151    5.6729    1.0420    0.5862    3.1558    0.0183
-#> 6:    92.6580    0.0258    2.3640    5.7014    0.9899    0.5569    3.0212    0.0140
-#> 7:    93.0532   -0.0754    2.2262    7.3582    0.9404    0.5291    2.5591    0.0180
-#> 8:    92.8372   -0.0760    2.2080    6.9903    0.8934    0.5026    2.5653    0.0187
-#> 9:    93.0757   -0.1322    2.1663    6.6408    0.8487    0.4775    2.4943    0.0182
-#> 10:    93.0704   -0.1520    2.1410    6.3087    0.8063    0.4536    2.4004    0.0225
-#> 11:    93.1611   -0.1366    2.1740    5.9933    0.7659    0.4309    2.4242    0.0199
-#> 12:    92.7195   -0.0787    2.2947    5.6936    0.7277    0.4094    2.4532    0.0205
-#> 13:    92.6573   -0.1543    2.1929    5.4089    0.6913    0.3889    2.3750    0.0244
-#> 14:    93.1138   -0.1547    2.1924    5.1385    0.6567    0.3695    2.3590    0.0187
-#> 15:    93.5083   -0.1625    2.1831    4.8816    0.6239    0.3510    2.4420    0.0125
-#> 16:    93.2086   -0.1667    2.1516    4.6375    0.5927    0.3334    2.4527    0.0004
-#> 17:    93.3988   -0.1766    2.1521    4.4056    0.5630    0.3168    2.4527    0.0004
-#> 18:    93.4526   -0.1748    2.1461    4.1853    0.5349    0.3009    2.3775    0.0116
-#> 19:    93.5953   -0.1963    2.1167    3.9761    0.5081    0.2859    2.4693    0.0031
-#> 20:    9.3404e+01  -2.4408e-01   2.0453e+00   3.7773e+00   4.8274e-01   2.7158e-01   2.4789e+00   2.0760e-05
-#> 21:    9.3624e+01  -2.4691e-01   2.0524e+00   3.5884e+00   4.5860e-01   2.5800e-01   2.4789e+00   2.0760e-05
-#> 22:    9.3821e+01  -2.5932e-01   2.0021e+00   3.4090e+00   4.3567e-01   2.8670e-01   2.4182e+00   9.3297e-06
-#> 23:    9.3572e+01  -2.3703e-01   2.0725e+00   3.2385e+00   4.4889e-01   2.7237e-01   2.4525e+00   1.5592e-06
-#> 24:    9.3496e+01  -2.2704e-01   2.0746e+00   3.0766e+00   4.3674e-01   2.5875e-01   2.4569e+00   6.1365e-05
-#> 25:    9.3772e+01  -2.2211e-01   2.0762e+00   2.9228e+00   4.4843e-01   2.6194e-01   2.4015e+00   8.3288e-05
-#> 26:    9.3266e+01  -1.9408e-01   2.1345e+00   2.7766e+00   4.6952e-01   2.4885e-01   2.3827e+00   2.9029e-05
-#> 27:    9.3472e+01  -1.9793e-01   2.1141e+00   3.5922e+00   4.7687e-01   2.3640e-01   2.3827e+00   2.9029e-05
-#> 28:    9.3411e+01  -1.7721e-01   2.1334e+00   3.4125e+00   4.8209e-01   2.2458e-01   2.3864e+00   6.5503e-06
-#> 29:    93.6868   -0.1863    2.1258    4.5379    0.4744    0.2134    2.3001    0.0045
-#> 30:    9.4054e+01  -1.8122e-01   2.1287e+00   4.9729e+00   4.7945e-01   2.0269e-01   2.2979e+00   5.8327e-05
-#> 31:    9.3955e+01  -1.9131e-01   2.1202e+00   5.6375e+00   4.7965e-01   1.9255e-01   2.2671e+00   1.6931e-05
-#> 32:    9.4376e+01  -1.6810e-01   2.1287e+00   5.3556e+00   4.7567e-01   1.8972e-01   2.2483e+00   1.1778e-05
-#> 33:    9.4067e+01  -1.5819e-01   2.1656e+00   5.0878e+00   4.5710e-01   1.9389e-01   2.2696e+00   2.4282e-05
-#> 34:    9.4526e+01  -1.6367e-01   2.1473e+00   4.8334e+00   4.7085e-01   1.8419e-01   2.2919e+00   8.8644e-06
-#> 35:    9.4972e+01  -1.6784e-01   2.1353e+00   4.5917e+00   4.7510e-01   1.7498e-01   2.3129e+00   2.2851e-05
-#> 36:    9.4744e+01  -1.5973e-01   2.1281e+00   5.2356e+00   4.5695e-01   1.8499e-01   2.2896e+00   6.8824e-05
-#> 37:    9.4721e+01  -1.6756e-01   2.1168e+00   5.1111e+00   4.6804e-01   1.8407e-01   2.3035e+00   1.5534e-06
-#> 38:    9.4613e+01  -1.5952e-01   2.1385e+00   4.8555e+00   4.6107e-01   1.7720e-01   2.2650e+00   1.2489e-05
-#> 39:    9.4787e+01  -1.6113e-01   2.1458e+00   4.6128e+00   4.6317e-01   1.8378e-01   2.2831e+00   1.3668e-05
-#> 40:    94.5315   -0.1765    2.1186    4.3821    0.4428    0.1902    2.3132    0.0001
-#> 41:    9.4336e+01  -1.8333e-01   2.1285e+00   4.1630e+00   4.4521e-01   1.9913e-01   2.3092e+00   1.3482e-05
-#> 42:    94.0780   -0.2031    2.0724    3.9549    0.4405    0.1892    2.2704    0.0056
-#> 43:    93.9276   -0.1896    2.1191    3.7571    0.4590    0.1797    2.2396    0.0080
-#> 44:    94.2491   -0.1896    2.1006    3.8473    0.4590    0.1764    2.2774    0.0083
-#> 45:    94.4073   -0.1811    2.1156    3.6550    0.4519    0.1676    2.2682    0.0078
-#> 46:    93.9736   -0.1882    2.1196    3.4722    0.4545    0.1633    2.2775    0.0035
-#> 47:    94.1930   -0.1965    2.1102    3.2986    0.4599    0.1664    2.3243    0.0005
-#> 48:    9.4147e+01  -1.9494e-01   2.1118e+00   3.3188e+00   4.7005e-01   1.7181e-01   2.3345e+00   1.1669e-05
-#> 49:    9.4139e+01  -1.7920e-01   2.1199e+00   3.1528e+00   4.7417e-01   1.6322e-01   2.2794e+00   3.5582e-05
-#> 50:    9.4031e+01  -1.9074e-01   2.1098e+00   2.9952e+00   4.7498e-01   1.6695e-01   2.2574e+00   2.7302e-06
-#> 51:    9.3982e+01  -1.9369e-01   2.1058e+00   2.8848e+00   4.8158e-01   1.8408e-01   2.2447e+00   1.8188e-05
-#> 52:    9.3924e+01  -2.0726e-01   2.0809e+00   3.6064e+00   4.7008e-01   2.0029e-01   2.2319e+00   6.8301e-06
-#> 53:    9.4094e+01  -1.9609e-01   2.0780e+00   4.4341e+00   4.7556e-01   1.9742e-01   2.2701e+00   2.1343e-06
-#> 54:    9.4351e+01  -1.9839e-01   2.0746e+00   4.2124e+00   4.7456e-01   1.8866e-01   2.2778e+00   4.8058e-06
-#> 55:    93.9450   -0.1876    2.1059    4.0017    0.4892    0.1792    2.2720    0.0001
-#> 56:    9.3741e+01  -1.8208e-01   2.1172e+00   3.8017e+00   4.7696e-01   1.7027e-01   2.2332e+00   2.1237e-05
-#> 57:    9.3668e+01  -1.8580e-01   2.1181e+00   3.9224e+00   4.7704e-01   1.7425e-01   2.2512e+00   2.2766e-05
-#> 58:    9.3811e+01  -1.8324e-01   2.1178e+00   3.7263e+00   4.7945e-01   1.7939e-01   2.2512e+00   2.2766e-05
-#> 59:    9.3800e+01  -1.6691e-01   2.1250e+00   3.8213e+00   4.9353e-01   1.8464e-01   2.2763e+00   4.6129e-06
-#> 60:    9.3997e+01  -1.5920e-01   2.1489e+00   3.6303e+00   5.0788e-01   1.7541e-01   2.2466e+00   4.1975e-06
-#> 61:    9.4215e+01  -1.6445e-01   2.1482e+00   3.9303e+00   5.1966e-01   1.6664e-01   2.3053e+00   5.8982e-07
-#> 62:    9.3936e+01  -1.6721e-01   2.1376e+00   4.0316e+00   5.3719e-01   1.7228e-01   2.2841e+00   7.8603e-05
-#> 63:    9.3832e+01  -1.6209e-01   2.1334e+00   3.8698e+00   5.4370e-01   1.7064e-01   2.3046e+00   6.4415e-07
-#> 64:    93.9042   -0.1617    2.1563    5.5384    0.5430    0.1622    2.2988    0.0002
-#> 65:    93.8613   -0.1723    2.1239    6.2143    0.5304    0.1541    2.2949    0.0001
-#> 66:    9.4113e+01  -1.9168e-01   2.1019e+00   7.3588e+00   5.1287e-01   1.4641e-01   2.3164e+00   1.2580e-05
-#> 67:    9.3954e+01  -1.8141e-01   2.1199e+00   6.9909e+00   5.0278e-01   1.4993e-01   2.2676e+00   1.1126e-05
-#> 68:    93.8741   -0.1852    2.1343    6.6414    0.4997    0.1493    2.2706    0.0001
-#> 69:    9.3657e+01  -1.8345e-01   2.1375e+00   6.3093e+00   5.0292e-01   1.6326e-01   2.2809e+00   1.7299e-07
-#> 70:    9.3762e+01  -1.7493e-01   2.1512e+00   5.9938e+00   5.1042e-01   1.5509e-01   2.2837e+00   4.5745e-05
-#> 71:    9.4060e+01  -1.6516e-01   2.1440e+00   5.6941e+00   5.1615e-01   1.4734e-01   2.3001e+00   3.9993e-07
-#> 72:    9.3927e+01  -1.7365e-01   2.1347e+00   5.4094e+00   5.2582e-01   1.3997e-01   2.3075e+00   6.3748e-06
-#> 73:    9.4049e+01  -1.8080e-01   2.1254e+00   5.1390e+00   5.1154e-01   1.3297e-01   2.3042e+00   9.5858e-06
-#> 74:    9.3917e+01  -1.9083e-01   2.1051e+00   4.8820e+00   5.0104e-01   1.4605e-01   2.2733e+00   7.4923e-05
-#> 75:    9.4271e+01  -1.8281e-01   2.1059e+00   5.0872e+00   5.0773e-01   1.5322e-01   2.2387e+00   1.4240e-05
-#> 76:    9.4205e+01  -1.8352e-01   2.1160e+00   4.8328e+00   5.0684e-01   1.5669e-01   2.2708e+00   3.6346e-05
-#> 77:    9.4480e+01  -1.8352e-01   2.0942e+00   4.9009e+00   5.0684e-01   1.4885e-01   2.3098e+00   1.8186e-06
-#> 78:    9.4699e+01  -1.9686e-01   2.0671e+00   4.6559e+00   4.9182e-01   1.4503e-01   2.2806e+00   7.9443e-08
-#> 79:    9.4785e+01  -2.0649e-01   2.0500e+00   6.0608e+00   4.6723e-01   1.6185e-01   2.2607e+00   2.1557e-07
-#> 80:    9.4782e+01  -2.0045e-01   2.0680e+00   5.7578e+00   4.5759e-01   1.5747e-01   2.2926e+00   8.6381e-06
-#> 81:    9.4339e+01  -2.0435e-01   2.0885e+00   6.9051e+00   4.5054e-01   1.7410e-01   2.2796e+00   1.5517e-05
-#> 82:    9.4805e+01  -2.1032e-01   2.0658e+00   7.1580e+00   4.7091e-01   1.6539e-01   2.3013e+00   1.3893e-05
-#> 83:    9.4650e+01  -2.0507e-01   2.0485e+00   6.8001e+00   4.7624e-01   1.5938e-01   2.3104e+00   6.6569e-06
-#> 84:    9.4766e+01  -1.9959e-01   2.0667e+00   6.4601e+00   4.7322e-01   1.5619e-01   2.3359e+00   1.8890e-09
-#> 85:    9.4714e+01  -1.9959e-01   2.0756e+00   6.1371e+00   4.7322e-01   1.6894e-01   2.2738e+00   4.9578e-06
-#> 86:    9.4466e+01  -2.0544e-01   2.0626e+00   5.8302e+00   4.6340e-01   1.6050e-01   2.2773e+00   3.6221e-07
-#> 87:    9.4786e+01  -1.9292e-01   2.0703e+00   5.5387e+00   4.6881e-01   1.5641e-01   2.2746e+00   2.3326e-05
-#> 88:    9.4573e+01  -1.9488e-01   2.0597e+00   5.2618e+00   4.6538e-01   1.5079e-01   2.3225e+00   4.7054e-05
-#> 89:    94.8466   -0.2040    2.0603    4.9987    0.4620    0.1456    2.2807    0.0002
-#> 90:    9.4839e+01  -2.0359e-01   2.0673e+00   4.7488e+00   4.5379e-01   1.4729e-01   2.3099e+00   2.7922e-05
-#> 91:    9.4897e+01  -2.0635e-01   2.0496e+00   4.5113e+00   4.4018e-01   1.3993e-01   2.2924e+00   1.7074e-05
-#> 92:    9.4740e+01  -2.0567e-01   2.0518e+00   4.2858e+00   4.6190e-01   1.3293e-01   2.3396e+00   9.0471e-05
-#> 93:    94.9558   -0.2033    2.0824    4.0715    0.4877    0.1263    2.3785    0.0082
-#> 94:    95.1673   -0.1801    2.0900    3.8679    0.5150    0.1200    2.4128    0.0106
-#> 95:    95.3129   -0.1686    2.1057    3.6745    0.4892    0.1140    2.4135    0.0147
-#> 96:    9.5235e+01  -1.6834e-01   2.1069e+00   3.4908e+00   4.9584e-01   1.0827e-01   2.4408e+00   2.5829e-06
-#> 97:    9.4892e+01  -1.5911e-01   2.1277e+00   3.3162e+00   4.7518e-01   1.0286e-01   2.4658e+00   1.8589e-05
-#> 98:    9.4749e+01  -1.6133e-01   2.1204e+00   4.5926e+00   4.6435e-01   1.0192e-01   2.4716e+00   5.8808e-09
-#> 99:    9.4546e+01  -1.5627e-01   2.1358e+00   5.5648e+00   4.8843e-01   1.0047e-01   2.5033e+00   2.5865e-05
-#> 100:    9.4544e+01  -1.6341e-01   2.1317e+00   5.2974e+00   4.7076e-01   1.1065e-01   2.4711e+00   4.4438e-05
-#> 101:    94.2461   -0.1640    2.1458    5.0325    0.4750    0.1107    2.5297    0.0002
-#> 102:    9.4039e+01  -1.6946e-01   2.1490e+00   4.9929e+00   4.7265e-01   1.2109e-01   2.3907e+00   2.3093e-05
-#> 103:    9.4132e+01  -1.6840e-01   2.1250e+00   5.3879e+00   4.7062e-01   1.2389e-01   2.3401e+00   5.4840e-07
-#> 104:    9.4376e+01  -1.6842e-01   2.1239e+00   7.9826e+00   4.7053e-01   1.1769e-01   2.3663e+00   1.9617e-05
-#> 105:    9.4370e+01  -1.7024e-01   2.1187e+00   7.5834e+00   4.6738e-01   1.1683e-01   2.3471e+00   1.4035e-05
-#> 106:    9.4462e+01  -1.6562e-01   2.1406e+00   7.5466e+00   4.6364e-01   1.2640e-01   2.3140e+00   4.7933e-05
-#> 107:    9.4541e+01  -1.6582e-01   2.1308e+00   7.1692e+00   4.6457e-01   1.2964e-01   2.3395e+00   1.8489e-05
-#> 108:    9.4709e+01  -1.6157e-01   2.1484e+00   6.8108e+00   4.5925e-01   1.3393e-01   2.3340e+00   1.5230e-06
-#> 109:    9.4450e+01  -1.8900e-01   2.0799e+00   6.4702e+00   4.4801e-01   1.4728e-01   2.3847e+00   3.2613e-05
-#> 110:    9.4180e+01  -1.9104e-01   2.1172e+00   6.1467e+00   4.5389e-01   1.4273e-01   2.3775e+00   6.0285e-05
-#> 111:    9.4366e+01  -1.8908e-01   2.1031e+00   5.8394e+00   4.4875e-01   1.4983e-01   2.3898e+00   7.2653e-05
-#> 112:    9.4008e+01  -1.8144e-01   2.1008e+00   5.5474e+00   4.6433e-01   1.4234e-01   2.3705e+00   9.9395e-06
-#> 113:    9.4372e+01  -1.8885e-01   2.1154e+00   5.2700e+00   4.7983e-01   1.3522e-01   2.3641e+00   1.8643e-05
-#> 114:    94.1292   -0.1872    2.1134    5.0065    0.4824    0.1285    2.3163    0.0001
-#> 115:    9.4510e+01  -1.7805e-01   2.1185e+00   4.7562e+00   4.8451e-01   1.2204e-01   2.3568e+00   1.6277e-07
-#> 116:    9.4234e+01  -1.8613e-01   2.1214e+00   4.5184e+00   4.7967e-01   1.2275e-01   2.3388e+00   3.4361e-05
-#> 117:    9.4438e+01  -1.7276e-01   2.1218e+00   4.2925e+00   4.6200e-01   1.1662e-01   2.3686e+00   5.6594e-06
-#> 118:    9.4498e+01  -1.7628e-01   2.1143e+00   6.2395e+00   4.5445e-01   1.2378e-01   2.3303e+00   6.5645e-05
-#> 119:    9.4303e+01  -1.8107e-01   2.1120e+00   7.5774e+00   4.6102e-01   1.2829e-01   2.3595e+00   9.4057e-06
-#> 120:    9.4022e+01  -1.7626e-01   2.1258e+00   9.9044e+00   4.6505e-01   1.5188e-01   2.3582e+00   3.6907e-05
-#> 121:    9.4103e+01  -1.5976e-01   2.1354e+00   9.4091e+00   4.7792e-01   1.5429e-01   2.3729e+00   4.6749e-05
-#> 122:    9.4727e+01  -1.9092e-01   2.0956e+00   8.9387e+00   4.5402e-01   1.6371e-01   2.3118e+00   6.8573e-06
-#> 123:    9.4447e+01  -1.9139e-01   2.0898e+00   8.4918e+00   4.3317e-01   1.7569e-01   2.3083e+00   4.4068e-05
-#> 124:    9.4422e+01  -1.9130e-01   2.0920e+00   8.0672e+00   4.3952e-01   1.7160e-01   2.3003e+00   1.7162e-05
-#> 125:    9.4608e+01  -1.7777e-01   2.1007e+00   7.6638e+00   4.8253e-01   1.6302e-01   2.3244e+00   1.9896e-05
-#> 126:    9.4512e+01  -1.6596e-01   2.1139e+00   7.2806e+00   4.7648e-01   1.7588e-01   2.2913e+00   4.9747e-05
-#> 127:    9.4983e+01  -1.6562e-01   2.1290e+00   6.9166e+00   4.7028e-01   1.6709e-01   2.3141e+00   3.3357e-05
-#> 128:    94.3910   -0.1728    2.1159    6.5708    0.4914    0.1850    2.3173    0.0001
-#> 129:    9.4578e+01  -1.7211e-01   2.1177e+00   6.2422e+00   4.8295e-01   1.7709e-01   2.2815e+00   4.8158e-05
-#> 130:    9.4646e+01  -1.6785e-01   2.1333e+00   5.9301e+00   4.6360e-01   1.6823e-01   2.3140e+00   2.1204e-05
-#> 131:    9.4670e+01  -1.4897e-01   2.1480e+00   5.6336e+00   4.8826e-01   1.5982e-01   2.3436e+00   1.3221e-05
-#> 132:    9.4625e+01  -1.6160e-01   2.1599e+00   5.3519e+00   4.6385e-01   1.6125e-01   2.2830e+00   9.6815e-06
-#> 133:    9.3985e+01  -1.7636e-01   2.1299e+00   5.8178e+00   4.4885e-01   1.5389e-01   2.2810e+00   6.7789e-06
-#> 134:    9.4105e+01  -1.7389e-01   2.1199e+00   5.5269e+00   4.5848e-01   1.4628e-01   2.2992e+00   7.6542e-06
-#> 135:    9.4387e+01  -1.5936e-01   2.1418e+00   5.2506e+00   4.5002e-01   1.6349e-01   2.3403e+00   7.6250e-05
-#> 136:    94.3595   -0.1696    2.1493    4.9880    0.4407    0.1722    2.3121    0.0001
-#> 137:    9.4056e+01  -1.6030e-01   2.1720e+00   5.5600e+00   4.4954e-01   1.8233e-01   2.3099e+00   2.1195e-05
-#> 138:    9.4043e+01  -1.4848e-01   2.1876e+00   5.2820e+00   4.5696e-01   1.8542e-01   2.2876e+00   8.7271e-06
-#> 139:    94.3020   -0.1374    2.1965    5.6428    0.4668    0.1927    2.3341    0.0001
-#> 140:    9.4260e+01  -1.3603e-01   2.2014e+00   5.7727e+00   4.6823e-01   1.8302e-01   2.3248e+00   1.4731e-06
-#> 141:    9.4302e+01  -1.2134e-01   2.1992e+00   5.4841e+00   4.8967e-01   1.7947e-01   2.3212e+00   1.6339e-05
-#> 142:    94.0970   -0.1143    2.2570    5.4173    0.4766    0.1726    2.3581    0.0077
-#> 143:    94.2078   -0.1162    2.2460    5.1464    0.4745    0.1874    2.3551    0.0152
-#> 144:    94.2085   -0.0953    2.2685    4.8891    0.5010    0.1780    2.3881    0.0095
-#> 145:    94.1483   -0.0906    2.2751    5.0705    0.4959    0.1770    2.3103    0.0143
-#> 146:    94.4257   -0.0859    2.2735    5.0201    0.5331    0.2050    2.3104    0.0160
-#> 147:    93.8072   -0.0887    2.2766    4.7691    0.5253    0.2200    2.2903    0.0180
-#> 148:    94.4354   -0.0901    2.2770    4.5306    0.5237    0.2147    2.3108    0.0150
-#> 149:    94.1171   -0.1126    2.2342    4.3041    0.5412    0.2300    2.3454    0.0126
-#> 150:    94.0704   -0.1267    2.2071    4.0889    0.5324    0.2185    2.3673    0.0097
-#> 151:    93.9860   -0.1480    2.1852    3.8844    0.5101    0.2529    2.3280    0.0056
-#> 152:    93.9500   -0.1419    2.1940    4.4687    0.5066    0.2371    2.3617    0.0002
-#> 153:    93.8058   -0.1368    2.1917    4.2493    0.5068    0.2057    2.3481    0.0002
-#> 154:    9.4043e+01  -1.3331e-01   2.1972e+00   4.3921e+00   4.7605e-01   1.9689e-01   2.3952e+00   9.5657e-05
-#> 155:    94.2500   -0.1223    2.2260    5.7786    0.4848    0.1829    2.3361    0.0075
-#> 156:    94.5035   -0.1223    2.2091    6.1344    0.4848    0.1558    2.3951    0.0048
-#> 157:    9.4448e+01  -1.3268e-01   2.1797e+00   6.4746e+00   4.6934e-01   1.6035e-01   2.3496e+00   5.2771e-05
-#> 158:    94.7438   -0.1401    2.1904    6.0162    0.4589    0.1692    2.3444    0.0001
-#> 159:    94.2681   -0.1430    2.1852    4.6165    0.4774    0.1617    2.3601    0.0001
-#> 160:    9.3911e+01  -1.1659e-01   2.2267e+00   4.9756e+00   4.9349e-01   1.7150e-01   2.3500e+00   9.0374e-06
-#> 161:    9.3914e+01  -1.1938e-01   2.2233e+00   4.8238e+00   4.9674e-01   1.8358e-01   2.3536e+00   1.1877e-06
-#> 162:    93.9974   -0.1188    2.2349    5.1092    0.4967    0.1714    2.3237    0.0041
-#> 163:    9.3939e+01  -1.2170e-01   2.2147e+00   4.8315e+00   5.0622e-01   1.8195e-01   2.3823e+00   2.4030e-05
-#> 164:    93.8015   -0.1362    2.2166    3.9112    0.4958    0.1684    2.3488    0.0072
-#> 165:    93.4082   -0.1398    2.2132    3.2992    0.5087    0.1734    2.2861    0.0125
-#> 166:    93.4680   -0.1421    2.2077    3.3232    0.5075    0.1643    2.2792    0.0149
-#> 167:    93.5455   -0.1443    2.2080    3.7465    0.4972    0.1685    2.2194    0.0191
-#> 168:    93.5603   -0.1711    2.1421    3.2407    0.5201    0.1940    2.3029    0.0198
-#> 169:    93.7281   -0.1578    2.1553    2.5110    0.4988    0.1836    2.3343    0.0134
-#> 170:    93.9675   -0.1564    2.1532    2.2507    0.5049    0.1753    2.3089    0.0110
-#> 171:    93.8255   -0.1543    2.1647    2.7302    0.5114    0.1691    2.2959    0.0113
-#> 172:    93.8071   -0.1536    2.1689    2.5849    0.5069    0.1751    2.3047    0.0099
-#> 173:    93.7137   -0.1403    2.2096    1.5160    0.5204    0.1622    2.3452    0.0155
-#> 174:    93.7182   -0.1376    2.1975    1.3366    0.5222    0.1700    2.3311    0.0149
-#> 175:    93.5957   -0.1587    2.1613    1.3539    0.5321    0.1470    2.3893    0.0156
-#> 176:    93.6058   -0.1587    2.1602    1.4588    0.5321    0.1412    2.4323    0.0116
-#> 177:    93.4496   -0.1858    2.1323    1.2423    0.4987    0.1460    2.3491    0.0167
-#> 178:    93.5894   -0.1935    2.1217    1.7812    0.4776    0.1643    2.3046    0.0168
-#> 179:    93.6386   -0.1887    2.1445    2.8813    0.4808    0.1585    2.2689    0.0192
-#> 180:    93.9288   -0.1950    2.1015    2.0905    0.4681    0.1557    2.2783    0.0170
-#> 181:    93.8165   -0.1950    2.0840    2.6302    0.4681    0.1592    2.3643    0.0173
-#> 182:    94.2132   -0.1936    2.0866    3.0185    0.5131    0.1712    2.3164    0.0147
-#> 183:    94.0929   -0.1896    2.0782    3.0716    0.5288    0.1644    2.5169    0.0066
-#> 184:    93.8694   -0.1968    2.0946    2.4734    0.5121    0.1709    2.3795    0.0071
-#> 185:    93.8138   -0.1970    2.0987    2.9707    0.4957    0.1500    2.3995    0.0034
-#> 186:    9.4047e+01  -2.1045e-01   2.0791e+00   3.6686e+00   4.8764e-01   1.4347e-01   2.3654e+00   3.8127e-05
-#> 187:    9.4498e+01  -1.9649e-01   2.0949e+00   2.0912e+00   4.7479e-01   1.6122e-01   2.3873e+00   4.7739e-06
-#> 188:    9.4650e+01  -1.8508e-01   2.1132e+00   2.1529e+00   4.6244e-01   1.4403e-01   2.3367e+00   3.5345e-06
-#> 189:    9.4301e+01  -1.8137e-01   2.1132e+00   2.6433e+00   4.4894e-01   1.3537e-01   2.3145e+00   9.6836e-06
-#> 190:    9.4501e+01  -1.8209e-01   2.0962e+00   3.1460e+00   4.4908e-01   1.2006e-01   2.3563e+00   3.3387e-05
-#> 191:    9.4156e+01  -2.0214e-01   2.0803e+00   3.2334e+00   4.7635e-01   1.1917e-01   2.3782e+00   6.6641e-06
-#> 192:    9.3981e+01  -2.1562e-01   2.0492e+00   3.0526e+00   5.0505e-01   1.3669e-01   2.3412e+00   7.3871e-05
-#> 193:    9.4085e+01  -2.2693e-01   2.0318e+00   2.9855e+00   4.9563e-01   1.4371e-01   2.3727e+00   8.6443e-05
-#> 194:    9.3922e+01  -2.3089e-01   2.0323e+00   2.9709e+00   4.9151e-01   1.4470e-01   2.3667e+00   3.5941e-05
-#> 195:    9.4180e+01  -2.2865e-01   2.0284e+00   2.2426e+00   4.8793e-01   1.5283e-01   2.3442e+00   1.8882e-05
-#> 196:    9.4259e+01  -2.0053e-01   2.0541e+00   1.5155e+00   5.1571e-01   1.5596e-01   2.3638e+00   2.9015e-05
-#> 197:    9.4225e+01  -2.0144e-01   2.0551e+00   1.6032e+00   5.0920e-01   1.6454e-01   2.3564e+00   2.7823e-05
-#> 198:    9.4166e+01  -1.9411e-01   2.0602e+00   1.8793e+00   5.5190e-01   1.8338e-01   2.3611e+00   1.6669e-05
-#> 199:    9.4230e+01  -1.9621e-01   2.0737e+00   1.8847e+00   5.4082e-01   1.7340e-01   2.3488e+00   5.8282e-07
-#> 200:    9.4215e+01  -1.9629e-01   2.0888e+00   1.9185e+00   5.4293e-01   1.7502e-01   2.3563e+00   5.7303e-06
-#> 201:    94.0654   -0.1931    2.0901    1.8074    0.5373    0.1886    2.3869    0.0025
-#> 202:    93.9801   -0.1898    2.0990    1.6823    0.5318    0.1841    2.4043    0.0016
-#> 203:    94.0246   -0.1893    2.1004    1.6503    0.5286    0.1855    2.3971    0.0012
-#> 204:    93.9893   -0.1870    2.1014    1.6166    0.5276    0.1846    2.3900    0.0010
-#> 205:    94.0154   -0.1854    2.1006    1.5294    0.5286    0.1828    2.3939    0.0009
-#> 206:    94.0468   -0.1833    2.1024    1.5102    0.5295    0.1807    2.3967    0.0007
-#> 207:    94.0641   -0.1810    2.1049    1.5136    0.5289    0.1798    2.4037    0.0008
-#> 208:    94.0794   -0.1790    2.1062    1.5078    0.5286    0.1790    2.4139    0.0007
-#> 209:    94.0892   -0.1799    2.1049    1.4549    0.5261    0.1793    2.4144    0.0006
-#> 210:    94.0911   -0.1817    2.1042    1.4537    0.5217    0.1810    2.4069    0.0012
-#> 211:    94.1011   -0.1828    2.1016    1.4582    0.5235    0.1825    2.4049    0.0011
-#> 212:    94.1081   -0.1839    2.0989    1.4657    0.5255    0.1838    2.4031    0.0010
-#> 213:    94.1264   -0.1842    2.0973    1.4527    0.5263    0.1851    2.4026    0.0010
-#> 214:    94.1287   -0.1844    2.0974    1.4405    0.5270    0.1869    2.4006    0.0009
-#> 215:    94.1440   -0.1850    2.0973    1.4556    0.5269    0.1876    2.3985    0.0009
-#> 216:    94.1352   -0.1863    2.0970    1.4698    0.5258    0.1885    2.3977    0.0008
-#> 217:    94.1261   -0.1868    2.0962    1.4850    0.5244    0.1897    2.3946    0.0008
-#> 218:    94.1100   -0.1858    2.0987    1.4673    0.5230    0.1934    2.3924    0.0007
-#> 219:    94.1073   -0.1845    2.1013    1.4630    0.5218    0.1993    2.3890    0.0011
-#> 220:    94.1026   -0.1836    2.1030    1.4705    0.5205    0.2028    2.3904    0.0010
-#> 221:    94.0972   -0.1824    2.1046    1.4732    0.5198    0.2065    2.3907    0.0010
-#> 222:    94.0898   -0.1824    2.1052    1.4952    0.5180    0.2083    2.3892    0.0010
-#> 223:    94.0975   -0.1830    2.1050    1.5035    0.5161    0.2107    2.3888    0.0011
-#> 224:    94.1027   -0.1831    2.1050    1.5196    0.5148    0.2124    2.3878    0.0011
-#> 225:    94.0977   -0.1828    2.1065    1.5153    0.5142    0.2141    2.3856    0.0013
-#> 226:    94.0907   -0.1831    2.1066    1.5287    0.5130    0.2151    2.3828    0.0014
-#> 227:    94.0831   -0.1833    2.1065    1.5535    0.5119    0.2159    2.3814    0.0014
-#> 228:    94.0834   -0.1832    2.1072    1.5713    0.5114    0.2174    2.3813    0.0014
-#> 229:    94.0793   -0.1832    2.1076    1.6041    0.5111    0.2184    2.3811    0.0015
-#> 230:    94.0701   -0.1843    2.1064    1.6177    0.5096    0.2181    2.3803    0.0017
-#> 231:    94.0598   -0.1853    2.1052    1.6254    0.5085    0.2180    2.3818    0.0016
-#> 232:    94.0539   -0.1862    2.1045    1.6254    0.5074    0.2175    2.3824    0.0017
-#> 233:    94.0498   -0.1869    2.1034    1.6380    0.5065    0.2169    2.3826    0.0017
-#> 234:    94.0514   -0.1872    2.1035    1.6300    0.5050    0.2160    2.3829    0.0017
-#> 235:    94.0521   -0.1876    2.1026    1.6263    0.5041    0.2148    2.3825    0.0018
-#> 236:    94.0587   -0.1876    2.1024    1.6277    0.5023    0.2134    2.3834    0.0020
-#> 237:    94.0741   -0.1873    2.1025    1.6349    0.5013    0.2120    2.3828    0.0019
-#> 238:    94.0898   -0.1876    2.1022    1.6509    0.4997    0.2107    2.3837    0.0019
-#> 239:    94.1055   -0.1880    2.1016    1.6596    0.4979    0.2098    2.3836    0.0018
-#> 240:    94.1209   -0.1885    2.1007    1.6627    0.4958    0.2092    2.3831    0.0018
-#> 241:    94.1322   -0.1893    2.0992    1.6563    0.4945    0.2085    2.3825    0.0017
-#> 242:    94.1404   -0.1904    2.0976    1.6574    0.4930    0.2082    2.3814    0.0017
-#> 243:    94.1428   -0.1914    2.0961    1.6412    0.4918    0.2078    2.3800    0.0017
-#> 244:    94.1477   -0.1923    2.0945    1.6287    0.4907    0.2071    2.3795    0.0016
-#> 245:    94.1525   -0.1931    2.0933    1.6225    0.4897    0.2064    2.3791    0.0016
-#> 246:    94.1557   -0.1938    2.0927    1.6243    0.4890    0.2048    2.3780    0.0016
-#> 247:    94.1576   -0.1943    2.0919    1.6333    0.4881    0.2034    2.3777    0.0015
-#> 248:    94.1603   -0.1951    2.0909    1.6328    0.4863    0.2026    2.3775    0.0015
-#> 249:    94.1648   -0.1957    2.0898    1.6427    0.4847    0.2018    2.3774    0.0015
-#> 250:    94.1766   -0.1963    2.0889    1.6482    0.4829    0.2012    2.3770    0.0015
-#> 251:    94.1854   -0.1971    2.0875    1.6536    0.4806    0.2011    2.3769    0.0016
-#> 252:    94.1906   -0.1980    2.0861    1.6527    0.4785    0.2013    2.3763    0.0017
-#> 253:    94.1913   -0.1982    2.0857    1.6459    0.4772    0.2014    2.3751    0.0019
-#> 254:    94.1945   -0.1985    2.0852    1.6413    0.4759    0.2019    2.3755    0.0019
-#> 255:    94.1972   -0.1989    2.0837    1.6451    0.4754    0.2027    2.3753    0.0018
-#> 256:    94.1994   -0.1989    2.0833    1.6548    0.4758    0.2024    2.3752    0.0018
-#> 257:    94.2014   -0.1987    2.0833    1.6708    0.4765    0.2024    2.3752    0.0018
-#> 258:    94.2081   -0.1984    2.0836    1.6903    0.4768    0.2023    2.3749    0.0017
-#> 259:    94.2151   -0.1982    2.0839    1.7169    0.4767    0.2023    2.3737    0.0017
-#> 260:    94.2212   -0.1980    2.0838    1.7426    0.4766    0.2031    2.3725    0.0017
-#> 261:    94.2229   -0.1981    2.0835    1.7696    0.4764    0.2038    2.3714    0.0017
-#> 262:    94.2213   -0.1983    2.0832    1.7977    0.4762    0.2045    2.3704    0.0016
-#> 263:    94.2220   -0.1984    2.0830    1.8277    0.4764    0.2051    2.3700    0.0016
-#> 264:    94.2230   -0.1983    2.0830    1.8430    0.4766    0.2057    2.3690    0.0016
-#> 265:    94.2235   -0.1983    2.0832    1.8679    0.4768    0.2060    2.3674    0.0016
-#> 266:    94.2242   -0.1982    2.0833    1.8705    0.4769    0.2064    2.3658    0.0015
-#> 267:    94.2267   -0.1982    2.0832    1.8715    0.4769    0.2070    2.3643    0.0015
-#> 268:    94.2312   -0.1980    2.0834    1.8824    0.4769    0.2074    2.3631    0.0015
-#> 269:    94.2329   -0.1981    2.0829    1.8843    0.4766    0.2084    2.3628    0.0015
-#> 270:    94.2321   -0.1982    2.0825    1.8904    0.4770    0.2093    2.3629    0.0015
-#> 271:    94.2349   -0.1985    2.0820    1.8942    0.4769    0.2101    2.3633    0.0016
-#> 272:    94.2388   -0.1989    2.0818    1.9099    0.4767    0.2110    2.3634    0.0018
-#> 273:    94.2420   -0.1992    2.0816    1.9259    0.4765    0.2118    2.3632    0.0018
-#> 274:    94.2454   -0.1994    2.0813    1.9330    0.4763    0.2128    2.3629    0.0017
-#> 275:    94.2456   -0.1997    2.0810    1.9316    0.4761    0.2138    2.3624    0.0018
-#> 276:    94.2472   -0.1999    2.0807    1.9306    0.4758    0.2146    2.3624    0.0019
-#> 277:    94.2492   -0.2001    2.0808    1.9326    0.4756    0.2153    2.3623    0.0020
-#> 278:    94.2493   -0.2003    2.0807    1.9225    0.4752    0.2163    2.3628    0.0020
-#> 279:    94.2481   -0.2002    2.0808    1.9206    0.4750    0.2168    2.3628    0.0019
-#> 280:    94.2433   -0.2002    2.0810    1.9257    0.4749    0.2173    2.3626    0.0019
-#> 281:    94.2358   -0.2004    2.0809    1.9217    0.4748    0.2173    2.3620    0.0019
-#> 282:    94.2307   -0.2005    2.0807    1.9209    0.4748    0.2172    2.3617    0.0019
-#> 283:    94.2302   -0.2008    2.0803    1.9131    0.4748    0.2172    2.3615    0.0019
-#> 284:    94.2309   -0.2009    2.0802    1.9085    0.4749    0.2171    2.3610    0.0018
-#> 285:    94.2344   -0.2010    2.0799    1.9135    0.4749    0.2170    2.3603    0.0018
-#> 286:    94.2381   -0.2013    2.0794    1.9099    0.4749    0.2167    2.3596    0.0018
-#> 287:    94.2420   -0.2016    2.0786    1.9105    0.4749    0.2164    2.3596    0.0018
-#> 288:    94.2425   -0.2020    2.0778    1.9081    0.4749    0.2161    2.3590    0.0019
-#> 289:    94.2386   -0.2023    2.0773    1.9136    0.4749    0.2158    2.3586    0.0019
-#> 290:    94.2357   -0.2026    2.0768    1.9171    0.4750    0.2154    2.3581    0.0019
-#> 291:    94.2326   -0.2026    2.0765    1.9162    0.4750    0.2150    2.3577    0.0019
-#> 292:    94.2305   -0.2026    2.0766    1.9178    0.4753    0.2144    2.3577    0.0020
-#> 293:    94.2268   -0.2023    2.0771    1.9257    0.4754    0.2138    2.3574    0.0022
-#> 294:    94.2216   -0.2023    2.0773    1.9326    0.4754    0.2132    2.3565    0.0023
-#> 295:    94.2193   -0.2024    2.0769    1.9378    0.4762    0.2125    2.3565    0.0024
-#> 296:    94.2160   -0.2025    2.0765    1.9463    0.4771    0.2117    2.3565    0.0025
-#> 297:    94.2106   -0.2026    2.0761    1.9523    0.4779    0.2109    2.3569    0.0026
-#> 298:    94.2089   -0.2028    2.0756    1.9622    0.4787    0.2099    2.3578    0.0025
-#> 299:    94.2077   -0.2029    2.0753    1.9721    0.4794    0.2090    2.3586    0.0026
-#> 300:    94.2064   -0.2030    2.0749    1.9838    0.4802    0.2080    2.3589    0.0026
-#> 301:    94.2086   -0.2029    2.0747    1.9942    0.4806    0.2071    2.3587    0.0025
-#> 302:    94.2111   -0.2031    2.0744    1.9938    0.4810    0.2063    2.3593    0.0025
-#> 303:    94.2133   -0.2031    2.0743    1.9923    0.4811    0.2056    2.3593    0.0025
-#> 304:    94.2151   -0.2032    2.0739    1.9885    0.4811    0.2049    2.3595    0.0025
-#> 305:    94.2159   -0.2035    2.0735    1.9872    0.4813    0.2044    2.3594    0.0024
-#> 306:    94.2192   -0.2038    2.0729    1.9806    0.4813    0.2041    2.3592    0.0024
-#> 307:    94.2226   -0.2040    2.0724    1.9796    0.4814    0.2038    2.3588    0.0024
-#> 308:    94.2224   -0.2042    2.0723    1.9828    0.4814    0.2036    2.3589    0.0024
-#> 309:    94.2200   -0.2043    2.0723    1.9859    0.4812    0.2034    2.3587    0.0024
-#> 310:    94.2183   -0.2044    2.0723    1.9892    0.4810    0.2034    2.3583    0.0023
-#> 311:    94.2175   -0.2044    2.0724    1.9895    0.4805    0.2033    2.3580    0.0023
-#> 312:    94.2171   -0.2044    2.0725    1.9977    0.4800    0.2032    2.3581    0.0023
-#> 313:    94.2108   -0.2044    2.0728    1.9995    0.4795    0.2030    2.3578    0.0023
-#> 314:    94.2068   -0.2045    2.0730    1.9929    0.4790    0.2029    2.3576    0.0024
-#> 315:    94.2031   -0.2047    2.0730    1.9884    0.4784    0.2028    2.3579    0.0024
-#> 316:    94.2018   -0.2048    2.0731    1.9860    0.4779    0.2026    2.3582    0.0024
-#> 317:    94.2015   -0.2050    2.0729    1.9836    0.4773    0.2025    2.3582    0.0024
-#> 318:    94.2025   -0.2052    2.0728    1.9814    0.4768    0.2024    2.3580    0.0023
-#> 319:    94.2066   -0.2053    2.0726    1.9867    0.4764    0.2024    2.3577    0.0023
-#> 320:    94.2074   -0.2055    2.0727    1.9896    0.4760    0.2024    2.3575    0.0023
-#> 321:    94.2097   -0.2055    2.0728    1.9985    0.4758    0.2026    2.3573    0.0023
-#> 322:    94.2080   -0.2054    2.0731    2.0108    0.4759    0.2028    2.3570    0.0023
-#> 323:    94.2042   -0.2054    2.0732    2.0253    0.4762    0.2030    2.3566    0.0023
-#> 324:    94.2005   -0.2054    2.0733    2.0514    0.4765    0.2032    2.3566    0.0023
-#> 325:    94.2000   -0.2053    2.0735    2.0719    0.4767    0.2034    2.3570    0.0023
-#> 326:    94.2002   -0.2052    2.0738    2.0907    0.4769    0.2034    2.3573    0.0023
-#> 327:    94.1997   -0.2051    2.0741    2.1140    0.4770    0.2035    2.3571    0.0023
-#> 328:    94.1976   -0.2050    2.0743    2.1379    0.4770    0.2035    2.3569    0.0023
-#> 329:    94.1969   -0.2051    2.0741    2.1485    0.4769    0.2038    2.3566    0.0022
-#> 330:    94.1959   -0.2053    2.0738    2.1533    0.4767    0.2042    2.3561    0.0022
-#> 331:    94.1962   -0.2055    2.0733    2.1588    0.4763    0.2046    2.3555    0.0022
-#> 332:    94.1967   -0.2059    2.0727    2.1626    0.4760    0.2051    2.3551    0.0022
-#> 333:    94.1964   -0.2062    2.0721    2.1666    0.4757    0.2056    2.3547    0.0022
-#> 334:    94.1978   -0.2064    2.0718    2.1703    0.4756    0.2063    2.3543    0.0022
-#> 335:    94.1985   -0.2066    2.0715    2.1698    0.4755    0.2068    2.3538    0.0021
-#> 336:    94.1999   -0.2068    2.0711    2.1705    0.4757    0.2075    2.3534    0.0021
-#> 337:    94.1990   -0.2069    2.0708    2.1690    0.4759    0.2080    2.3530    0.0021
-#> 338:    94.1965   -0.2071    2.0706    2.1708    0.4760    0.2085    2.3525    0.0021
-#> 339:    94.1934   -0.2071    2.0704    2.1769    0.4761    0.2088    2.3518    0.0021
-#> 340:    94.1908   -0.2072    2.0704    2.1794    0.4763    0.2091    2.3515    0.0021
-#> 341:    94.1875   -0.2072    2.0706    2.1859    0.4762    0.2092    2.3512    0.0021
-#> 342:    94.1840   -0.2071    2.0707    2.1903    0.4762    0.2093    2.3513    0.0021
-#> 343:    94.1816   -0.2072    2.0706    2.1909    0.4761    0.2093    2.3512    0.0020
-#> 344:    94.1815   -0.2070    2.0708    2.1877    0.4758    0.2091    2.3514    0.0021
-#> 345:    94.1839   -0.2070    2.0710    2.1844    0.4757    0.2090    2.3517    0.0021
-#> 346:    94.1868   -0.2068    2.0713    2.1787    0.4756    0.2088    2.3520    0.0020
-#> 347:    94.1871   -0.2066    2.0717    2.1762    0.4756    0.2086    2.3519    0.0020
-#> 348:    94.1868   -0.2064    2.0722    2.1724    0.4756    0.2084    2.3521    0.0020
-#> 349:    94.1892   -0.2062    2.0725    2.1673    0.4755    0.2080    2.3524    0.0020
-#> 350:    94.1921   -0.2060    2.0726    2.1632    0.4754    0.2076    2.3527    0.0020
-#> 351:    94.1947   -0.2060    2.0726    2.1613    0.4752    0.2073    2.3530    0.0020
-#> 352:    94.1988   -0.2060    2.0725    2.1647    0.4751    0.2069    2.3530    0.0020
-#> 353:    94.2036   -0.2061    2.0721    2.1684    0.4749    0.2067    2.3530    0.0020
-#> 354:    94.2082   -0.2061    2.0719    2.1670    0.4747    0.2063    2.3529    0.0020
-#> 355:    94.2111   -0.2061    2.0718    2.1645    0.4747    0.2062    2.3526    0.0020
-#> 356:    94.2123   -0.2061    2.0717    2.1628    0.4747    0.2063    2.3525    0.0020
-#> 357:    94.2146   -0.2062    2.0716    2.1610    0.4746    0.2064    2.3523    0.0020
-#> 358:    94.2161   -0.2062    2.0715    2.1656    0.4744    0.2065    2.3520    0.0020
-#> 359:    94.2178   -0.2063    2.0714    2.1684    0.4743    0.2065    2.3516    0.0020
-#> 360:    94.2194   -0.2063    2.0713    2.1687    0.4742    0.2065    2.3512    0.0019
-#> 361:    94.2191   -0.2064    2.0713    2.1738    0.4741    0.2065    2.3508    0.0019
-#> 362:    94.2186   -0.2064    2.0713    2.1762    0.4740    0.2065    2.3502    0.0019
-#> 363:    94.2179   -0.2064    2.0714    2.1754    0.4740    0.2065    2.3495    0.0019
-#> 364:    94.2165   -0.2063    2.0715    2.1740    0.4741    0.2064    2.3495    0.0019
-#> 365:    94.2149   -0.2063    2.0716    2.1736    0.4741    0.2062    2.3495    0.0020
-#> 366:    94.2141   -0.2062    2.0717    2.1813    0.4740    0.2064    2.3490    0.0020
-#> 367:    94.2158   -0.2062    2.0717    2.1905    0.4739    0.2063    2.3491    0.0019
-#> 368:    94.2173   -0.2062    2.0718    2.1963    0.4737    0.2063    2.3485    0.0019
-#> 369:    94.2183   -0.2062    2.0717    2.2005    0.4736    0.2064    2.3481    0.0019
-#> 370:    94.2194   -0.2062    2.0716    2.2016    0.4735    0.2063    2.3477    0.0019
-#> 371:    94.2192   -0.2063    2.0715    2.1997    0.4733    0.2064    2.3476    0.0019
-#> 372:    94.2202   -0.2062    2.0716    2.1957    0.4733    0.2065    2.3479    0.0019
-#> 373:    94.2208   -0.2061    2.0717    2.1913    0.4733    0.2065    2.3480    0.0019
-#> 374:    94.2209   -0.2061    2.0719    2.1870    0.4731    0.2065    2.3479    0.0019
-#> 375:    94.2219   -0.2061    2.0719    2.1864    0.4729    0.2064    2.3477    0.0019
-#> 376:    94.2231   -0.2061    2.0720    2.1849    0.4726    0.2063    2.3473    0.0019
-#> 377:    94.2251   -0.2061    2.0720    2.1835    0.4724    0.2063    2.3471    0.0019
-#> 378:    94.2238   -0.2062    2.0719    2.1777    0.4721    0.2062    2.3472    0.0018
-#> 379:    94.2226   -0.2064    2.0717    2.1741    0.4717    0.2063    2.3471    0.0018
-#> 380:    94.2216   -0.2066    2.0714    2.1759    0.4714    0.2063    2.3468    0.0018
-#> 381:    94.2206   -0.2068    2.0711    2.1784    0.4711    0.2063    2.3465    0.0018
-#> 382:    94.2200   -0.2071    2.0707    2.1753    0.4707    0.2062    2.3462    0.0018
-#> 383:    94.2205   -0.2073    2.0704    2.1757    0.4703    0.2061    2.3461    0.0018
-#> 384:    94.2201   -0.2076    2.0702    2.1802    0.4698    0.2060    2.3458    0.0018
-#> 385:    94.2210   -0.2078    2.0701    2.1795    0.4693    0.2061    2.3457    0.0018
-#> 386:    94.2199   -0.2079    2.0700    2.1788    0.4688    0.2061    2.3455    0.0018
-#> 387:    94.2181   -0.2081    2.0699    2.1801    0.4683    0.2061    2.3454    0.0018
-#> 388:    94.2169   -0.2082    2.0699    2.1850    0.4679    0.2061    2.3452    0.0017
-#> 389:    94.2158   -0.2083    2.0699    2.1881    0.4674    0.2063    2.3449    0.0017
-#> 390:    94.2162   -0.2084    2.0696    2.1928    0.4671    0.2064    2.3447    0.0017
-#> 391:    94.2172   -0.2085    2.0696    2.1921    0.4669    0.2063    2.3444    0.0017
-#> 392:    94.2175   -0.2085    2.0695    2.1933    0.4667    0.2063    2.3442    0.0017
-#> 393:    94.2174   -0.2086    2.0695    2.1972    0.4666    0.2062    2.3440    0.0017
-#> 394:    94.2179   -0.2087    2.0694    2.1972    0.4664    0.2061    2.3439    0.0017
-#> 395:    94.2200   -0.2087    2.0694    2.2009    0.4663    0.2059    2.3438    0.0017
-#> 396:    94.2189   -0.2086    2.0695    2.2062    0.4662    0.2058    2.3434    0.0017
-#> 397:    94.2183   -0.2085    2.0696    2.2151    0.4663    0.2056    2.3431    0.0017
-#> 398:    94.2186   -0.2085    2.0696    2.2200    0.4664    0.2056    2.3430    0.0017
-#> 399:    94.2183   -0.2084    2.0698    2.2204    0.4664    0.2056    2.3428    0.0017
-#> 400:    94.2184   -0.2082    2.0703    2.2252    0.4665    0.2054    2.3428    0.0016
-#> 401:    94.2176   -0.2080    2.0707    2.2323    0.4666    0.2052    2.3427    0.0016
-#> 402:    94.2167   -0.2078    2.0712    2.2397    0.4668    0.2050    2.3426    0.0016
-#> 403:    94.2157   -0.2075    2.0716    2.2464    0.4669    0.2049    2.3426    0.0016
-#> 404:    94.2152   -0.2074    2.0719    2.2508    0.4670    0.2047    2.3427    0.0016
-#> 405:    94.2152   -0.2072    2.0723    2.2537    0.4671    0.2046    2.3427    0.0016
-#> 406:    94.2151   -0.2070    2.0726    2.2565    0.4672    0.2044    2.3427    0.0016
-#> 407:    94.2132   -0.2067    2.0731    2.2568    0.4673    0.2044    2.3426    0.0016
-#> 408:    94.2142   -0.2065    2.0734    2.2579    0.4674    0.2046    2.3424    0.0016
-#> 409:    94.2136   -0.2063    2.0738    2.2630    0.4674    0.2046    2.3420    0.0016
-#> 410:    94.2125   -0.2062    2.0739    2.2635    0.4674    0.2047    2.3417    0.0016
-#> 411:    94.2131   -0.2061    2.0741    2.2634    0.4674    0.2048    2.3413    0.0016
-#> 412:    94.2132   -0.2060    2.0742    2.2662    0.4674    0.2048    2.3409    0.0016
-#> 413:    94.2143   -0.2059    2.0743    2.2666    0.4673    0.2048    2.3407    0.0016
-#> 414:    94.2156   -0.2058    2.0743    2.2710    0.4672    0.2048    2.3404    0.0015
-#> 415:    94.2174   -0.2057    2.0745    2.2751    0.4671    0.2049    2.3400    0.0015
-#> 416:    94.2185   -0.2057    2.0746    2.2762    0.4669    0.2049    2.3399    0.0015
-#> 417:    94.2208   -0.2056    2.0748    2.2759    0.4667    0.2049    2.3397    0.0015
-#> 418:    94.2231   -0.2054    2.0751    2.2772    0.4664    0.2050    2.3398    0.0015
-#> 419:    94.2249   -0.2053    2.0754    2.2783    0.4663    0.2050    2.3396    0.0015
-#> 420:    94.2255   -0.2052    2.0757    2.2798    0.4660    0.2050    2.3395    0.0015
-#> 421:    94.2265   -0.2051    2.0759    2.2848    0.4659    0.2050    2.3392    0.0016
-#> 422:    94.2288   -0.2049    2.0761    2.2929    0.4659    0.2050    2.3390    0.0016
-#> 423:    94.2307   -0.2048    2.0762    2.2988    0.4657    0.2051    2.3390    0.0016
-#> 424:    94.2313   -0.2047    2.0764    2.3017    0.4656    0.2051    2.3391    0.0016
-#> 425:    94.2322   -0.2046    2.0765    2.3028    0.4655    0.2050    2.3388    0.0016
-#> 426:    94.2327   -0.2046    2.0765    2.3049    0.4654    0.2050    2.3386    0.0016
-#> 427:    94.2323   -0.2045    2.0768    2.3053    0.4655    0.2049    2.3386    0.0016
-#> 428:    94.2324   -0.2044    2.0770    2.3016    0.4655    0.2048    2.3387    0.0017
-#> 429:    94.2322   -0.2043    2.0772    2.2984    0.4656    0.2047    2.3386    0.0017
-#> 430:    94.2306   -0.2042    2.0774    2.2971    0.4656    0.2046    2.3384    0.0017
-#> 431:    94.2295   -0.2042    2.0775    2.2931    0.4657    0.2044    2.3384    0.0017
-#> 432:    94.2298   -0.2040    2.0778    2.2896    0.4656    0.2044    2.3383    0.0018
-#> 433:    94.2311   -0.2039    2.0780    2.2885    0.4656    0.2044    2.3383    0.0018
-#> 434:    94.2311   -0.2037    2.0783    2.2854    0.4655    0.2044    2.3381    0.0018
-#> 435:    94.2314   -0.2036    2.0786    2.2838    0.4654    0.2044    2.3378    0.0018
-#> 436:    94.2315   -0.2035    2.0788    2.2817    0.4653    0.2044    2.3377    0.0018
-#> 437:    94.2326   -0.2034    2.0790    2.2801    0.4652    0.2044    2.3378    0.0018
-#> 438:    94.2338   -0.2034    2.0791    2.2802    0.4650    0.2046    2.3380    0.0018
-#> 439:    94.2340   -0.2033    2.0791    2.2810    0.4649    0.2046    2.3377    0.0018
-#> 440:    94.2330   -0.2034    2.0791    2.2822    0.4646    0.2046    2.3376    0.0018
-#> 441:    94.2323   -0.2035    2.0790    2.2818    0.4644    0.2046    2.3375    0.0018
-#> 442:    94.2321   -0.2034    2.0792    2.2804    0.4642    0.2043    2.3375    0.0018
-#> 443:    94.2313   -0.2033    2.0794    2.2812    0.4641    0.2041    2.3372    0.0018
-#> 444:    94.2301   -0.2032    2.0796    2.2820    0.4640    0.2040    2.3369    0.0018
-#> 445:    94.2279   -0.2031    2.0799    2.2872    0.4639    0.2039    2.3366    0.0018
-#> 446:    94.2272   -0.2030    2.0801    2.2874    0.4639    0.2037    2.3363    0.0018
-#> 447:    94.2262   -0.2029    2.0803    2.2881    0.4639    0.2036    2.3359    0.0018
-#> 448:    94.2248   -0.2028    2.0806    2.2905    0.4639    0.2036    2.3358    0.0018
-#> 449:    94.2245   -0.2027    2.0808    2.2914    0.4638    0.2035    2.3356    0.0018
-#> 450:    94.2237   -0.2027    2.0809    2.2928    0.4638    0.2035    2.3356    0.0018
-#> 451:    94.2233   -0.2025    2.0813    2.2917    0.4639    0.2033    2.3355    0.0018
-#> 452:    94.2232   -0.2023    2.0816    2.2898    0.4640    0.2031    2.3356    0.0018
-#> 453:    94.2230   -0.2021    2.0819    2.2890    0.4641    0.2030    2.3356    0.0018
-#> 454:    94.2222   -0.2020    2.0822    2.2851    0.4641    0.2029    2.3357    0.0018
-#> 455:    94.2214   -0.2018    2.0824    2.2820    0.4640    0.2028    2.3357    0.0017
-#> 456:    94.2212   -0.2017    2.0827    2.2797    0.4640    0.2026    2.3357    0.0017
-#> 457:    94.2216   -0.2016    2.0829    2.2771    0.4640    0.2024    2.3358    0.0017
-#> 458:    94.2220   -0.2015    2.0831    2.2740    0.4639    0.2022    2.3358    0.0017
-#> 459:    94.2229   -0.2013    2.0834    2.2765    0.4638    0.2021    2.3358    0.0017
-#> 460:    94.2226   -0.2012    2.0837    2.2810    0.4637    0.2020    2.3359    0.0017
-#> 461:    94.2227   -0.2009    2.0841    2.2893    0.4637    0.2018    2.3358    0.0017
-#> 462:    94.2235   -0.2007    2.0844    2.2942    0.4637    0.2016    2.3357    0.0017
-#> 463:    94.2241   -0.2005    2.0848    2.2971    0.4637    0.2014    2.3358    0.0017
-#> 464:    94.2236   -0.2002    2.0853    2.2953    0.4637    0.2012    2.3360    0.0017
-#> 465:    94.2230   -0.2000    2.0858    2.2946    0.4638    0.2010    2.3360    0.0017
-#> 466:    94.2215   -0.1997    2.0863    2.2995    0.4638    0.2009    2.3363    0.0017
-#> 467:    94.2193   -0.1995    2.0868    2.3051    0.4637    0.2008    2.3363    0.0017
-#> 468:    94.2174   -0.1992    2.0874    2.3086    0.4636    0.2006    2.3363    0.0018
-#> 469:    94.2160   -0.1989    2.0881    2.3072    0.4636    0.2006    2.3361    0.0018
-#> 470:    94.2152   -0.1985    2.0887    2.3075    0.4637    0.2005    2.3363    0.0018
-#> 471:    94.2139   -0.1982    2.0891    2.3126    0.4638    0.2004    2.3361    0.0018
-#> 472:    94.2134   -0.1980    2.0895    2.3151    0.4640    0.2002    2.3360    0.0018
-#> 473:    94.2141   -0.1979    2.0897    2.3149    0.4640    0.2001    2.3360    0.0018
-#> 474:    94.2144   -0.1978    2.0900    2.3140    0.4640    0.2001    2.3358    0.0018
-#> 475:    94.2151   -0.1977    2.0901    2.3151    0.4640    0.2000    2.3358    0.0018
-#> 476:    94.2154   -0.1975    2.0903    2.3195    0.4641    0.2001    2.3357    0.0018
-#> 477:    94.2167   -0.1974    2.0905    2.3253    0.4642    0.2002    2.3358    0.0018
-#> 478:    94.2163   -0.1972    2.0909    2.3324    0.4641    0.2004    2.3357    0.0017
-#> 479:    94.2156   -0.1970    2.0912    2.3364    0.4640    0.2006    2.3355    0.0017
-#> 480:    94.2149   -0.1969    2.0915    2.3395    0.4638    0.2007    2.3353    0.0017
-#> 481:    94.2140   -0.1968    2.0918    2.3431    0.4637    0.2008    2.3350    0.0017
-#> 482:    94.2137   -0.1967    2.0919    2.3440    0.4635    0.2010    2.3349    0.0017
-#> 483:    94.2139   -0.1966    2.0920    2.3468    0.4634    0.2011    2.3348    0.0017
-#> 484:    94.2149   -0.1966    2.0921    2.3488    0.4633    0.2012    2.3346    0.0017
-#> 485:    94.2153   -0.1966    2.0921    2.3486    0.4632    0.2012    2.3345    0.0017
-#> 486:    94.2148   -0.1965    2.0923    2.3483    0.4631    0.2015    2.3345    0.0017
-#> 487:    94.2140   -0.1965    2.0923    2.3492    0.4628    0.2018    2.3345    0.0017
-#> 488:    94.2121   -0.1965    2.0923    2.3489    0.4625    0.2020    2.3347    0.0017
-#> 489:    94.2119   -0.1966    2.0923    2.3497    0.4622    0.2023    2.3346    0.0017
-#> 490:    94.2120   -0.1966    2.0923    2.3476    0.4618    0.2025    2.3346    0.0017
-#> 491:    94.2124   -0.1966    2.0923    2.3462    0.4615    0.2028    2.3346    0.0017
-#> 492:    94.2118   -0.1966    2.0923    2.3453    0.4613    0.2029    2.3346    0.0017
-#> 493:    94.2113   -0.1967    2.0923    2.3452    0.4610    0.2030    2.3347    0.0017
-#> 494:    94.2118   -0.1968    2.0922    2.3488    0.4608    0.2030    2.3347    0.0017
-#> 495:    94.2122   -0.1969    2.0920    2.3530    0.4605    0.2029    2.3347    0.0017
-#> 496:    94.2138   -0.1969    2.0919    2.3540    0.4603    0.2028    2.3350    0.0017
-#> 497:    94.2148   -0.1970    2.0917    2.3554    0.4601    0.2029    2.3352    0.0017
-#> 498:    94.2152   -0.1971    2.0916    2.3534    0.4600    0.2029    2.3356    0.0017
-#> 499:    94.2157   -0.1972    2.0914    2.3519    0.4598    0.2029    2.3357    0.0016
-#> 500:    94.2162   -0.1973    2.0912    2.3498    0.4596    0.2030    2.3358    0.0016
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 | log_alpha |  log_beta | sigma_low |
-#> |.....................|  rsd_high |        o1 |        o2 |        o3 |
-#> |    1|     356.08238 |     1.000 |    -1.000 |   -0.9495 |   -0.9739 |
-#> |.....................|   -0.9969 |   -0.9818 |   -0.9750 |   -0.9744 |
-#> |    U|     356.08238 |     93.10 |   -0.1209 |     2.232 |     1.095 |
-#> |.....................|   0.02509 |    0.7272 |     1.045 |     1.072 |
-#> |    X|     356.08238 |     93.10 |    0.8861 |     9.321 |     1.095 |
-#> |.....................|   0.02509 |    0.7272 |     1.045 |     1.072 |
-#> |    G|    Gill Diff. |    -85.81 |    0.5929 |    0.9043 |    -97.79 |
-#> |.....................|    -28.71 |  -0.07427 |    -8.550 |    -12.99 |
-#> |    2|     1940.7752 |     1.640 |    -1.004 |   -0.9563 |   -0.2449 |
-#> |.....................|   -0.7829 |   -0.9813 |   -0.9112 |   -0.8775 |
-#> |    U|     1940.7752 |     152.7 |   -0.1253 |     2.226 |     1.495 |
-#> |.....................|   0.02778 |    0.7276 |     1.112 |     1.176 |
-#> |    X|     1940.7752 |     152.7 |    0.8822 |     9.258 |     1.495 |
-#> |.....................|   0.02778 |    0.7276 |     1.112 |     1.176 |
-#> |    3|     370.78508 |     1.064 |    -1.000 |   -0.9502 |   -0.9010 |
-#> |.....................|   -0.9755 |   -0.9817 |   -0.9686 |   -0.9647 |
-#> |    U|     370.78508 |     99.05 |   -0.1213 |     2.232 |     1.135 |
-#> |.....................|   0.02536 |    0.7272 |     1.052 |     1.082 |
-#> |    X|     370.78508 |     99.05 |    0.8857 |     9.315 |     1.135 |
-#> |.....................|   0.02536 |    0.7272 |     1.052 |     1.082 |
-#> |    4|     354.52588 |     1.015 |    -1.000 |   -0.9497 |   -0.9565 |
-#> |.....................|   -0.9918 |   -0.9818 |   -0.9735 |   -0.9721 |
-#> |    U|     354.52588 |     94.52 |   -0.1210 |     2.232 |     1.105 |
-#> |.....................|   0.02516 |    0.7272 |     1.047 |     1.074 |
-#> |    X|     354.52588 |     94.52 |    0.8860 |     9.319 |     1.105 |
-#> |.....................|   0.02516 |    0.7272 |     1.047 |     1.074 |
-#> |    F| Forward Diff. |     126.3 |    0.7329 |     1.391 |    -95.71 |
-#> |.....................|    -26.58 |    0.4812 |    -8.528 |    -12.76 |
-#> |    5|     352.43362 |    0.9998 |    -1.000 |   -0.9499 |   -0.9392 |
-#> |.....................|   -0.9869 |   -0.9819 |   -0.9719 |   -0.9698 |
-#> |    U|     352.43362 |     93.08 |   -0.1211 |     2.232 |     1.114 |
-#> |.....................|   0.02522 |    0.7271 |     1.048 |     1.077 |
-#> |    X|     352.43362 |     93.08 |    0.8859 |     9.317 |     1.114 |
-#> |.....................|   0.02522 |    0.7271 |     1.048 |     1.077 |
-#> |    F| Forward Diff. |    -88.58 |    0.5971 |    0.9141 |    -92.65 |
-#> |.....................|    -26.61 |  -0.01862 |    -8.458 |    -12.78 |
-#> |    6|     350.82994 |     1.015 |    -1.000 |   -0.9501 |   -0.9214 |
-#> |.....................|   -0.9818 |   -0.9819 |   -0.9703 |   -0.9673 |
-#> |    U|     350.82994 |     94.46 |   -0.1213 |     2.232 |     1.124 |
-#> |.....................|   0.02528 |    0.7271 |     1.050 |     1.079 |
-#> |    X|     350.82994 |     94.46 |    0.8858 |     9.315 |     1.124 |
-#> |.....................|   0.02528 |    0.7271 |     1.050 |     1.079 |
-#> |    F| Forward Diff. |     115.7 |    0.7442 |     1.407 |    -90.51 |
-#> |.....................|    -24.67 |    0.2416 |    -8.378 |    -12.59 |
-#> |    7|     348.85697 |     1.000 |    -1.000 |   -0.9503 |   -0.9035 |
-#> |.....................|   -0.9769 |   -0.9819 |   -0.9686 |   -0.9649 |
-#> |    U|     348.85697 |     93.10 |   -0.1214 |     2.231 |     1.134 |
-#> |.....................|   0.02534 |    0.7271 |     1.052 |     1.082 |
-#> |    X|     348.85697 |     93.10 |    0.8857 |     9.313 |     1.134 |
-#> |.....................|   0.02534 |    0.7271 |     1.052 |     1.082 |
-#> |    F| Forward Diff. |    -86.89 |    0.6078 |    0.9395 |    -87.49 |
-#> |.....................|    -24.70 |   -0.2033 |    -8.301 |    -12.59 |
-#> |    8|     347.23757 |     1.014 |    -1.001 |   -0.9506 |   -0.8852 |
-#> |.....................|   -0.9717 |   -0.9819 |   -0.9669 |   -0.9622 |
-#> |    U|     347.23757 |     94.41 |   -0.1215 |     2.231 |     1.144 |
-#> |.....................|   0.02541 |    0.7271 |     1.054 |     1.085 |
-#> |    X|     347.23757 |     94.41 |    0.8856 |     9.311 |     1.144 |
-#> |.....................|   0.02541 |    0.7271 |     1.054 |     1.085 |
-#> |    F| Forward Diff. |     106.0 |    0.7499 |     1.419 |    -85.67 |
-#> |.....................|    -22.89 |  -0.09812 |    -8.213 |    -12.39 |
-#> |    9|     345.37317 |     1.000 |    -1.001 |   -0.9508 |   -0.8667 |
-#> |.....................|   -0.9667 |   -0.9818 |   -0.9651 |   -0.9596 |
-#> |    U|     345.37317 |     93.12 |   -0.1217 |     2.231 |     1.154 |
-#> |.....................|   0.02547 |    0.7272 |     1.056 |     1.088 |
-#> |    X|     345.37317 |     93.12 |    0.8854 |     9.308 |     1.154 |
-#> |.....................|   0.02547 |    0.7272 |     1.056 |     1.088 |
-#> |    F| Forward Diff. |    -84.47 |    0.6193 |    0.9668 |    -82.72 |
-#> |.....................|    -22.87 |   -0.2860 |    -8.128 |    -12.38 |
-#> |   10|     343.77522 |     1.014 |    -1.001 |   -0.9511 |   -0.8479 |
-#> |.....................|   -0.9616 |   -0.9818 |   -0.9633 |   -0.9568 |
-#> |    U|     343.77522 |     94.37 |   -0.1218 |     2.231 |     1.164 |
-#> |.....................|   0.02554 |    0.7272 |     1.057 |     1.091 |
-#> |    X|     343.77522 |     94.37 |    0.8853 |     9.306 |     1.164 |
-#> |.....................|   0.02554 |    0.7272 |     1.057 |     1.091 |
-#> |    F| Forward Diff. |     98.54 |    0.7582 |     1.440 |    -80.80 |
-#> |.....................|    -21.11 |   -0.2480 |    -8.037 |    -12.18 |
-#> |   11|     342.01002 |     1.000 |    -1.001 |   -0.9514 |   -0.8290 |
-#> |.....................|   -0.9566 |   -0.9817 |   -0.9614 |   -0.9539 |
-#> |    U|     342.01002 |     93.14 |   -0.1220 |     2.230 |     1.175 |
-#> |.....................|   0.02560 |    0.7273 |     1.059 |     1.094 |
-#> |    X|     342.01002 |     93.14 |    0.8852 |     9.303 |     1.175 |
-#> |.....................|   0.02560 |    0.7273 |     1.059 |     1.094 |
-#> |    F| Forward Diff. |    -81.78 |    0.6281 |    0.9934 |    -78.17 |
-#> |.....................|    -21.11 |   -0.4903 |    -7.943 |    -12.16 |
-#> |   12|     340.43696 |     1.013 |    -1.001 |   -0.9517 |   -0.8098 |
-#> |.....................|   -0.9515 |   -0.9816 |   -0.9595 |   -0.9509 |
-#> |    U|     340.43696 |     94.32 |   -0.1222 |     2.230 |     1.185 |
-#> |.....................|   0.02566 |    0.7274 |     1.062 |     1.097 |
-#> |    X|     340.43696 |     94.32 |    0.8850 |     9.301 |     1.185 |
-#> |.....................|   0.02566 |    0.7274 |     1.062 |     1.097 |
-#> |    F| Forward Diff. |     90.87 |    0.7671 |     1.462 |    -75.86 |
-#> |.....................|    -19.30 |   -0.2119 |    -7.851 |    -11.96 |
-#> |   13|     338.78414 |     1.001 |    -1.001 |   -0.9520 |   -0.7906 |
-#> |.....................|   -0.9465 |   -0.9815 |   -0.9574 |   -0.9478 |
-#> |    U|     338.78414 |     93.15 |   -0.1223 |     2.230 |     1.196 |
-#> |.....................|   0.02572 |    0.7274 |     1.064 |     1.100 |
-#> |    X|     338.78414 |     93.15 |    0.8848 |     9.298 |     1.196 |
-#> |.....................|   0.02572 |    0.7274 |     1.064 |     1.100 |
-#> |    F| Forward Diff. |    -80.47 |    0.6431 |     1.023 |    -73.28 |
-#> |.....................|    -19.27 |   -0.2791 |    -7.739 |    -11.92 |
-#> |   14|     337.22825 |     1.013 |    -1.002 |   -0.9523 |   -0.7710 |
-#> |.....................|   -0.9415 |   -0.9814 |   -0.9553 |   -0.9445 |
-#> |    U|     337.22825 |     94.28 |   -0.1225 |     2.229 |     1.206 |
-#> |.....................|   0.02579 |    0.7275 |     1.066 |     1.104 |
-#> |    X|     337.22825 |     94.28 |    0.8847 |     9.295 |     1.206 |
-#> |.....................|   0.02579 |    0.7275 |     1.066 |     1.104 |
-#> |    F| Forward Diff. |     82.17 |    0.7754 |     1.480 |    -71.69 |
-#> |.....................|    -17.81 |   -0.5846 |    -7.635 |    -11.71 |
-#> |   15|     335.66851 |     1.001 |    -1.002 |   -0.9527 |   -0.7512 |
-#> |.....................|   -0.9367 |   -0.9812 |   -0.9531 |   -0.9411 |
-#> |    U|     335.66851 |     93.18 |   -0.1228 |     2.229 |     1.217 |
-#> |.....................|   0.02585 |    0.7276 |     1.068 |     1.108 |
-#> |    X|     335.66851 |     93.18 |    0.8845 |     9.291 |     1.217 |
-#> |.....................|   0.02585 |    0.7276 |     1.068 |     1.108 |
-#> |    F| Forward Diff. |    -77.03 |    0.6546 |     1.055 |    -69.28 |
-#> |.....................|    -17.76 |   -0.6126 |    -7.531 |    -11.66 |
-#> |   16|     334.17549 |     1.012 |    -1.002 |   -0.9531 |   -0.7314 |
-#> |.....................|   -0.9319 |   -0.9810 |   -0.9509 |   -0.9376 |
-#> |    U|     334.17549 |     94.25 |   -0.1230 |     2.229 |     1.228 |
-#> |.....................|   0.02591 |    0.7278 |     1.070 |     1.111 |
-#> |    X|     334.17549 |     94.25 |    0.8843 |     9.287 |     1.228 |
-#> |.....................|   0.02591 |    0.7278 |     1.070 |     1.111 |
-#> |    F| Forward Diff. |     77.34 |    0.7869 |     1.511 |    -67.40 |
-#> |.....................|    -16.23 |   -0.6338 |    -7.414 |    -11.45 |
-#> |   17|     332.70253 |     1.001 |    -1.002 |   -0.9536 |   -0.7113 |
-#> |.....................|   -0.9273 |   -0.9807 |   -0.9485 |   -0.9339 |
-#> |    U|     332.70253 |     93.20 |   -0.1232 |     2.228 |     1.239 |
-#> |.....................|   0.02597 |    0.7280 |     1.073 |     1.115 |
-#> |    X|     332.70253 |     93.20 |    0.8841 |     9.283 |     1.239 |
-#> |.....................|   0.02597 |    0.7280 |     1.073 |     1.115 |
-#> |    F| Forward Diff. |    -74.42 |    0.6680 |     1.089 |    -65.07 |
-#> |.....................|    -16.20 |   -0.6067 |    -7.288 |    -11.39 |
-#> |   18|     331.26057 |     1.012 |    -1.003 |   -0.9540 |   -0.6912 |
-#> |.....................|   -0.9227 |   -0.9804 |   -0.9461 |   -0.9301 |
-#> |    U|     331.26057 |     94.22 |   -0.1235 |     2.228 |     1.250 |
-#> |.....................|   0.02602 |    0.7282 |     1.076 |     1.119 |
-#> |    X|     331.26057 |     94.22 |    0.8838 |     9.279 |     1.250 |
-#> |.....................|   0.02602 |    0.7282 |     1.076 |     1.119 |
-#> |    F| Forward Diff. |     71.33 |    0.7962 |     1.537 |    -63.45 |
-#> |.....................|    -14.84 |   -0.8466 |    -7.169 |    -11.16 |
-#> |   19|     329.86877 |     1.001 |    -1.003 |   -0.9546 |   -0.6708 |
-#> |.....................|   -0.9184 |   -0.9799 |   -0.9435 |   -0.9260 |
-#> |    U|     329.86877 |     93.23 |   -0.1238 |     2.227 |     1.261 |
-#> |.....................|   0.02608 |    0.7285 |     1.078 |     1.124 |
-#> |    X|     329.86877 |     93.23 |    0.8836 |     9.273 |     1.261 |
-#> |.....................|   0.02608 |    0.7285 |     1.078 |     1.124 |
-#> |    F| Forward Diff. |    -70.96 |    0.6825 |     1.126 |    -60.92 |
-#> |.....................|    -14.66 |   -0.5289 |    -7.027 |    -11.08 |
-#> |   20|     328.50031 |     1.012 |    -1.003 |   -0.9552 |   -0.6504 |
-#> |.....................|   -0.9143 |   -0.9795 |   -0.9408 |   -0.9217 |
-#> |    U|     328.50031 |     94.20 |   -0.1241 |     2.227 |     1.272 |
-#> |.....................|   0.02613 |    0.7288 |     1.081 |     1.128 |
-#> |    X|     328.50031 |     94.20 |    0.8833 |     9.268 |     1.272 |
-#> |.....................|   0.02613 |    0.7288 |     1.081 |     1.128 |
-#> |    F| Forward Diff. |     67.86 |    0.8082 |     1.577 |    -59.49 |
-#> |.....................|    -13.42 |   -0.7986 |    -6.899 |    -10.84 |
-#> |   21|     327.16645 |     1.002 |    -1.004 |   -0.9559 |   -0.6298 |
-#> |.....................|   -0.9105 |   -0.9791 |   -0.9380 |   -0.9171 |
-#> |    U|     327.16645 |     93.27 |   -0.1245 |     2.226 |     1.284 |
-#> |.....................|   0.02618 |    0.7291 |     1.084 |     1.133 |
-#> |    X|     327.16645 |     93.27 |    0.8829 |     9.261 |     1.284 |
-#> |.....................|   0.02618 |    0.7291 |     1.084 |     1.133 |
-#> |    F| Forward Diff. |    -65.39 |    0.6978 |     1.172 |    -57.48 |
-#> |.....................|    -13.36 |   -0.7754 |    -6.743 |    -10.73 |
-#> |   22|     325.87373 |     1.012 |    -1.004 |   -0.9567 |   -0.6091 |
-#> |.....................|   -0.9070 |   -0.9785 |   -0.9351 |   -0.9123 |
-#> |    U|     325.87373 |     94.19 |   -0.1249 |     2.225 |     1.295 |
-#> |.....................|   0.02622 |    0.7296 |     1.087 |     1.138 |
-#> |    X|     325.87373 |     94.19 |    0.8826 |     9.255 |     1.295 |
-#> |.....................|   0.02622 |    0.7296 |     1.087 |     1.138 |
-#> |    F| Forward Diff. |     64.00 |    0.8187 |     1.613 |    -55.46 |
-#> |.....................|    -12.01 |   -0.6347 |    -6.615 |    -10.48 |
-#> |   23|     324.62990 |     1.002 |    -1.004 |   -0.9576 |   -0.5884 |
-#> |.....................|   -0.9040 |   -0.9780 |   -0.9320 |   -0.9071 |
-#> |    U|      324.6299 |     93.29 |   -0.1254 |     2.224 |     1.306 |
-#> |.....................|   0.02626 |    0.7300 |     1.090 |     1.144 |
-#> |    X|      324.6299 |     93.29 |    0.8822 |     9.246 |     1.306 |
-#> |.....................|   0.02626 |    0.7300 |     1.090 |     1.144 |
-#> |    F| Forward Diff. |    -64.25 |    0.7091 |     1.205 |    -53.86 |
-#> |.....................|    -12.06 |   -0.7132 |    -6.446 |    -10.35 |
-#> |   24|     323.37595 |     1.011 |    -1.005 |   -0.9586 |   -0.5676 |
-#> |.....................|   -0.9015 |   -0.9774 |   -0.9287 |   -0.9014 |
-#> |    U|     323.37595 |     94.14 |   -0.1259 |     2.223 |     1.318 |
-#> |.....................|   0.02629 |    0.7304 |     1.094 |     1.150 |
-#> |    X|     323.37595 |     94.14 |    0.8817 |     9.236 |     1.318 |
-#> |.....................|   0.02629 |    0.7304 |     1.094 |     1.150 |
-#> |    F| Forward Diff. |     56.04 |    0.8254 |     1.637 |    -52.44 |
-#> |.....................|    -10.96 |   -0.9420 |    -6.280 |    -10.07 |
-#> |   25|     322.22752 |     1.002 |    -1.006 |   -0.9598 |   -0.5467 |
-#> |.....................|   -0.8995 |   -0.9764 |   -0.9254 |   -0.8957 |
-#> |    U|     322.22752 |     93.30 |   -0.1265 |     2.222 |     1.329 |
-#> |.....................|   0.02631 |    0.7311 |     1.097 |     1.156 |
-#> |    X|     322.22752 |     93.30 |    0.8812 |     9.225 |     1.329 |
-#> |.....................|   0.02631 |    0.7311 |     1.097 |     1.156 |
-#> |    F| Forward Diff. |    -62.58 |    0.7198 |     1.238 |    -50.46 |
-#> |.....................|    -10.85 |   -0.6563 |    -6.111 |    -9.931 |
-#> |   26|     321.05050 |     1.011 |    -1.006 |   -0.9612 |   -0.5258 |
-#> |.....................|   -0.8983 |   -0.9755 |   -0.9219 |   -0.8894 |
-#> |    U|      321.0505 |     94.13 |   -0.1272 |     2.221 |     1.341 |
-#> |.....................|   0.02633 |    0.7318 |     1.101 |     1.163 |
-#> |    X|      321.0505 |     94.13 |    0.8805 |     9.213 |     1.341 |
-#> |.....................|   0.02633 |    0.7318 |     1.101 |     1.163 |
-#> |    F| Forward Diff. |     53.55 |    0.8319 |     1.674 |    -49.18 |
-#> |.....................|    -9.827 |   -0.8926 |    -5.944 |    -9.631 |
-#> |   27|     319.96320 |     1.003 |    -1.007 |   -0.9629 |   -0.5048 |
-#> |.....................|   -0.8978 |   -0.9744 |   -0.9184 |   -0.8829 |
-#> |    U|      319.9632 |     93.35 |   -0.1280 |     2.219 |     1.352 |
-#> |.....................|   0.02633 |    0.7325 |     1.104 |     1.170 |
-#> |    X|      319.9632 |     93.35 |    0.8798 |     9.197 |     1.352 |
-#> |.....................|   0.02633 |    0.7325 |     1.104 |     1.170 |
-#> |    F| Forward Diff. |    -57.14 |    0.7318 |     1.284 |    -47.52 |
-#> |.....................|    -9.778 |   -0.7040 |    -5.744 |    -9.448 |
-#> |   28|     318.87595 |     1.011 |    -1.008 |   -0.9647 |   -0.4840 |
-#> |.....................|   -0.8984 |   -0.9733 |   -0.9148 |   -0.8761 |
-#> |    U|     318.87595 |     94.12 |   -0.1289 |     2.217 |     1.364 |
-#> |.....................|   0.02633 |    0.7334 |     1.108 |     1.177 |
-#> |    X|     318.87595 |     94.12 |    0.8790 |     9.180 |     1.364 |
-#> |.....................|   0.02633 |    0.7334 |     1.108 |     1.177 |
-#> |    F| Forward Diff. |     50.84 |    0.8352 |     1.706 |    -46.29 |
-#> |.....................|    -8.837 |   -0.9158 |    -5.564 |    -9.134 |
-#> |   29|     317.86528 |     1.003 |    -1.009 |   -0.9669 |   -0.4631 |
-#> |.....................|   -0.9000 |   -0.9719 |   -0.9113 |   -0.8691 |
-#> |    U|     317.86528 |     93.39 |   -0.1300 |     2.215 |     1.375 |
-#> |.....................|   0.02631 |    0.7344 |     1.112 |     1.185 |
-#> |    X|     317.86528 |     93.39 |    0.8781 |     9.160 |     1.375 |
-#> |.....................|   0.02631 |    0.7344 |     1.112 |     1.185 |
-#> |    F| Forward Diff. |    -53.64 |    0.7337 |     1.307 |    -44.73 |
-#> |.....................|    -8.788 |   -0.7242 |    -5.380 |    -8.940 |
-#> |   30|     316.86653 |     1.011 |    -1.010 |   -0.9694 |   -0.4424 |
-#> |.....................|   -0.9029 |   -0.9703 |   -0.9078 |   -0.8619 |
-#> |    U|     316.86653 |     94.11 |   -0.1312 |     2.212 |     1.386 |
-#> |.....................|   0.02627 |    0.7355 |     1.115 |     1.192 |
-#> |    X|     316.86653 |     94.11 |    0.8771 |     9.137 |     1.386 |
-#> |.....................|   0.02627 |    0.7355 |     1.115 |     1.192 |
-#> |    F| Forward Diff. |     47.91 |    0.8298 |     1.717 |    -43.37 |
-#> |.....................|    -7.860 |   -0.7095 |    -5.221 |    -8.628 |
-#> |   31|     315.94581 |     1.003 |    -1.012 |   -0.9723 |   -0.4219 |
-#> |.....................|   -0.9070 |   -0.9693 |   -0.9044 |   -0.8547 |
-#> |    U|     315.94581 |     93.42 |   -0.1325 |     2.209 |     1.398 |
-#> |.....................|   0.02622 |    0.7363 |     1.119 |     1.200 |
-#> |    X|     315.94581 |     93.42 |    0.8759 |     9.111 |     1.398 |
-#> |.....................|   0.02622 |    0.7363 |     1.119 |     1.200 |
-#> |    F| Forward Diff. |    -50.84 |    0.7268 |     1.307 |    -41.97 |
-#> |.....................|    -7.840 |   -0.5502 |    -5.032 |    -8.421 |
-#> |   32|     315.03994 |     1.011 |    -1.013 |   -0.9754 |   -0.4018 |
-#> |.....................|   -0.9129 |   -0.9687 |   -0.9011 |   -0.8473 |
-#> |    U|     315.03994 |     94.09 |   -0.1340 |     2.206 |     1.409 |
-#> |.....................|   0.02615 |    0.7367 |     1.122 |     1.208 |
-#> |    X|     315.03994 |     94.09 |    0.8746 |     9.082 |     1.409 |
-#> |.....................|   0.02615 |    0.7367 |     1.122 |     1.208 |
-#> |    F| Forward Diff. |     43.50 |    0.8139 |     1.698 |    -41.38 |
-#> |.....................|    -7.196 |   -0.9249 |    -4.882 |    -8.108 |
-#> |   33|     314.20198 |     1.004 |    -1.015 |   -0.9788 |   -0.3816 |
-#> |.....................|   -0.9197 |   -0.9671 |   -0.8983 |   -0.8406 |
-#> |    U|     314.20198 |     93.47 |   -0.1355 |     2.203 |     1.420 |
-#> |.....................|   0.02606 |    0.7379 |     1.125 |     1.215 |
-#> |    X|     314.20198 |     93.47 |    0.8733 |     9.052 |     1.420 |
-#> |.....................|   0.02606 |    0.7379 |     1.125 |     1.215 |
-#> |    F| Forward Diff. |    -46.04 |    0.7133 |     1.286 |    -40.35 |
-#> |.....................|    -7.243 |   -0.8268 |    -4.724 |    -7.917 |
-#> |   34|     313.39087 |     1.011 |    -1.016 |   -0.9822 |   -0.3616 |
-#> |.....................|   -0.9277 |   -0.9641 |   -0.8960 |   -0.8348 |
-#> |    U|     313.39087 |     94.10 |   -0.1371 |     2.200 |     1.431 |
-#> |.....................|   0.02596 |    0.7401 |     1.128 |     1.221 |
-#> |    X|     313.39087 |     94.10 |    0.8719 |     9.021 |     1.431 |
-#> |.....................|   0.02596 |    0.7401 |     1.128 |     1.221 |
-#> |    F| Forward Diff. |     42.44 |    0.7936 |     1.657 |    -38.93 |
-#> |.....................|    -6.417 |   -0.6060 |    -4.631 |    -7.687 |
-#> |   35|     312.65204 |     1.004 |    -1.018 |   -0.9857 |   -0.3421 |
-#> |.....................|   -0.9371 |   -0.9626 |   -0.8936 |   -0.8290 |
-#> |    U|     312.65204 |     93.49 |   -0.1387 |     2.196 |     1.441 |
-#> |.....................|   0.02584 |    0.7411 |     1.130 |     1.228 |
-#> |    X|     312.65204 |     93.49 |    0.8705 |     8.989 |     1.441 |
-#> |.....................|   0.02584 |    0.7411 |     1.130 |     1.228 |
-#> |    F| Forward Diff. |    -46.74 |    0.6875 |     1.233 |    -38.07 |
-#> |.....................|    -6.520 |   -0.5247 |    -4.495 |    -7.518 |
-#> |   36|     311.92333 |     1.010 |    -1.020 |   -0.9894 |   -0.3235 |
-#> |.....................|   -0.9483 |   -0.9627 |   -0.8910 |   -0.8230 |
-#> |    U|     311.92333 |     94.07 |   -0.1404 |     2.192 |     1.452 |
-#> |.....................|   0.02570 |    0.7411 |     1.133 |     1.234 |
-#> |    X|     311.92333 |     94.07 |    0.8690 |     8.957 |     1.452 |
-#> |.....................|   0.02570 |    0.7411 |     1.133 |     1.234 |
-#> |    F| Forward Diff. |     35.63 |    0.7624 |     1.583 |    -37.23 |
-#> |.....................|    -5.893 |   -0.6222 |    -4.382 |    -7.287 |
-#> |   37|     311.27355 |     1.004 |    -1.021 |   -0.9929 |   -0.3046 |
-#> |.....................|   -0.9595 |   -0.9623 |   -0.8888 |   -0.8177 |
-#> |    U|     311.27355 |     93.51 |   -0.1420 |     2.189 |     1.462 |
-#> |.....................|   0.02556 |    0.7413 |     1.135 |     1.240 |
-#> |    X|     311.27355 |     93.51 |    0.8676 |     8.925 |     1.462 |
-#> |.....................|   0.02556 |    0.7413 |     1.135 |     1.240 |
-#> |    F| Forward Diff. |    -45.98 |    0.6631 |     1.170 |    -36.31 |
-#> |.....................|    -5.950 |   -0.4376 |    -4.255 |    -7.133 |
-#> |   38|     310.62439 |     1.010 |    -1.023 |   -0.9963 |   -0.2868 |
-#> |.....................|   -0.9728 |   -0.9625 |   -0.8869 |   -0.8128 |
-#> |    U|     310.62439 |     94.07 |   -0.1437 |     2.185 |     1.472 |
-#> |.....................|   0.02539 |    0.7412 |     1.137 |     1.245 |
-#> |    X|     310.62439 |     94.07 |    0.8661 |     8.895 |     1.472 |
-#> |.....................|   0.02539 |    0.7412 |     1.137 |     1.245 |
-#> |    F| Forward Diff. |     33.19 |    0.7369 |     1.513 |    -35.63 |
-#> |.....................|    -5.399 |   -0.5527 |    -4.174 |    -6.950 |
-#> |   39|     310.04420 |     1.005 |    -1.024 |   -0.9995 |   -0.2687 |
-#> |.....................|   -0.9859 |   -0.9628 |   -0.8850 |   -0.8081 |
-#> |    U|      310.0442 |     93.55 |   -0.1453 |     2.182 |     1.482 |
-#> |.....................|   0.02523 |    0.7410 |     1.139 |     1.250 |
-#> |    X|      310.0442 |     93.55 |    0.8648 |     8.866 |     1.482 |
-#> |.....................|   0.02523 |    0.7410 |     1.139 |     1.250 |
-#> |    F| Forward Diff. |    -43.63 |    0.6390 |     1.117 |    -34.92 |
-#> |.....................|    -5.491 |   -0.4082 |    -4.072 |    -6.814 |
-#> |   40|     309.46411 |     1.010 |    -1.026 |    -1.003 |   -0.2518 |
-#> |.....................|    -1.001 |   -0.9632 |   -0.8835 |   -0.8040 |
-#> |    U|     309.46411 |     94.07 |   -0.1468 |     2.179 |     1.491 |
-#> |.....................|   0.02504 |    0.7407 |     1.141 |     1.254 |
-#> |    X|     309.46411 |     94.07 |    0.8634 |     8.839 |     1.491 |
-#> |.....................|   0.02504 |    0.7407 |     1.141 |     1.254 |
-#> |    F| Forward Diff. |     30.94 |    0.7075 |     1.451 |    -34.14 |
-#> |.....................|    -4.970 |   -0.4915 |    -4.021 |    -6.668 |
-#> |   41|     308.94397 |     1.005 |    -1.027 |    -1.005 |   -0.2344 |
-#> |.....................|    -1.015 |   -0.9639 |   -0.8817 |   -0.7999 |
-#> |    U|     308.94397 |     93.57 |   -0.1483 |     2.176 |     1.500 |
-#> |.....................|   0.02486 |    0.7402 |     1.143 |     1.259 |
-#> |    X|     308.94397 |     93.57 |    0.8622 |     8.814 |     1.500 |
-#> |.....................|   0.02486 |    0.7402 |     1.143 |     1.259 |
-#> |    F| Forward Diff. |    -43.40 |    0.6150 |     1.062 |    -33.15 |
-#> |.....................|    -4.981 |   -0.1275 |    -3.914 |    -6.542 |
-#> |   42|     308.42636 |     1.010 |    -1.029 |    -1.008 |   -0.2188 |
-#> |.....................|    -1.031 |   -0.9663 |   -0.8797 |   -0.7956 |
-#> |    U|     308.42636 |     94.07 |   -0.1498 |     2.174 |     1.509 |
-#> |.....................|   0.02466 |    0.7384 |     1.145 |     1.264 |
-#> |    X|     308.42636 |     94.07 |    0.8609 |     8.789 |     1.509 |
-#> |.....................|   0.02466 |    0.7384 |     1.145 |     1.264 |
-#> |    F| Forward Diff. |     28.94 |    0.6832 |     1.395 |    -33.36 |
-#> |.....................|    -4.720 |   -0.6585 |    -3.841 |    -6.387 |
-#> |   43|     307.94294 |     1.006 |    -1.030 |    -1.011 |   -0.2019 |
-#> |.....................|    -1.047 |   -0.9672 |   -0.8783 |   -0.7922 |
-#> |    U|     307.94294 |     93.62 |   -0.1511 |     2.171 |     1.518 |
-#> |.....................|   0.02447 |    0.7378 |     1.146 |     1.267 |
-#> |    X|     307.94294 |     93.62 |    0.8597 |     8.766 |     1.518 |
-#> |.....................|   0.02447 |    0.7378 |     1.146 |     1.267 |
-#> |    F| Forward Diff. |    -38.44 |    0.5985 |     1.037 |    -32.41 |
-#> |.....................|    -4.734 |   -0.3663 |    -3.762 |    -6.284 |
-#> |   44|     307.46797 |     1.011 |    -1.032 |    -1.013 |   -0.1861 |
-#> |.....................|    -1.063 |   -0.9666 |   -0.8774 |   -0.7896 |
-#> |    U|     307.46797 |     94.11 |   -0.1524 |     2.169 |     1.527 |
-#> |.....................|   0.02426 |    0.7383 |     1.147 |     1.270 |
-#> |    X|     307.46797 |     94.11 |    0.8586 |     8.746 |     1.527 |
-#> |.....................|   0.02426 |    0.7383 |     1.147 |     1.270 |
-#> |    F| Forward Diff. |     31.70 |    0.6652 |     1.367 |    -32.07 |
-#> |.....................|    -4.364 |   -0.4841 |    -3.739 |    -6.200 |
-#> |   45|     307.02197 |     1.006 |    -1.033 |    -1.016 |   -0.1702 |
-#> |.....................|    -1.080 |   -0.9671 |   -0.8762 |   -0.7866 |
-#> |    U|     307.02197 |     93.66 |   -0.1537 |     2.166 |     1.536 |
-#> |.....................|   0.02405 |    0.7379 |     1.149 |     1.273 |
-#> |    X|     307.02197 |     93.66 |    0.8575 |     8.725 |     1.536 |
-#> |.....................|   0.02405 |    0.7379 |     1.149 |     1.273 |
-#> |    F| Forward Diff. |    -34.81 |    0.5817 |     1.015 |    -31.25 |
-#> |.....................|    -4.413 |   -0.2597 |    -3.670 |    -6.117 |
-#> |   46|     306.58875 |     1.011 |    -1.034 |    -1.018 |   -0.1551 |
-#> |.....................|    -1.097 |   -0.9684 |   -0.8747 |   -0.7833 |
-#> |    U|     306.58875 |     94.13 |   -0.1549 |     2.164 |     1.544 |
-#> |.....................|   0.02384 |    0.7369 |     1.150 |     1.277 |
-#> |    X|     306.58875 |     94.13 |    0.8565 |     8.705 |     1.544 |
-#> |.....................|   0.02384 |    0.7369 |     1.150 |     1.277 |
-#> |    F| Forward Diff. |     31.47 |    0.6484 |     1.332 |    -31.08 |
-#> |.....................|    -4.101 |   -0.4354 |    -3.617 |    -5.999 |
-#> |   47|     306.17343 |     1.006 |    -1.035 |    -1.020 |   -0.1399 |
-#> |.....................|    -1.114 |   -0.9699 |   -0.8732 |   -0.7802 |
-#> |    U|     306.17343 |     93.70 |   -0.1561 |     2.162 |     1.552 |
-#> |.....................|   0.02362 |    0.7358 |     1.152 |     1.280 |
-#> |    X|     306.17343 |     93.70 |    0.8554 |     8.686 |     1.552 |
-#> |.....................|   0.02362 |    0.7358 |     1.152 |     1.280 |
-#> |    F| Forward Diff. |    -31.81 |    0.5683 |    0.9956 |    -30.69 |
-#> |.....................|    -4.225 |   -0.4059 |    -3.540 |    -5.903 |
-#> |   48|     305.76609 |     1.011 |    -1.036 |    -1.022 |   -0.1248 |
-#> |.....................|    -1.132 |   -0.9702 |   -0.8722 |   -0.7778 |
-#> |    U|     305.76609 |     94.14 |   -0.1573 |     2.160 |     1.560 |
-#> |.....................|   0.02340 |    0.7356 |     1.153 |     1.283 |
-#> |    X|     305.76609 |     94.14 |    0.8545 |     8.668 |     1.560 |
-#> |.....................|   0.02340 |    0.7356 |     1.153 |     1.283 |
-#> |    F| Forward Diff. |     30.78 |    0.6301 |     1.297 |    -30.24 |
-#> |.....................|    -3.891 |   -0.4278 |    -3.502 |    -5.825 |
-#> |   49|     305.37620 |     1.007 |    -1.037 |    -1.024 |   -0.1098 |
-#> |.....................|    -1.149 |   -0.9705 |   -0.8714 |   -0.7755 |
-#> |    U|      305.3762 |     93.72 |   -0.1584 |     2.158 |     1.569 |
-#> |.....................|   0.02318 |    0.7354 |     1.154 |     1.285 |
-#> |    X|      305.3762 |     93.72 |    0.8535 |     8.651 |     1.569 |
-#> |.....................|   0.02318 |    0.7354 |     1.154 |     1.285 |
-#> |    F| Forward Diff. |    -32.45 |    0.5512 |    0.9611 |    -29.28 |
-#> |.....................|    -3.904 |  -0.09870 |    -3.459 |    -5.767 |
-#> |   50|     304.99974 |     1.011 |    -1.039 |    -1.026 |  -0.09561 |
-#> |.....................|    -1.167 |   -0.9731 |   -0.8699 |   -0.7723 |
-#> |    U|     304.99974 |     94.15 |   -0.1595 |     2.156 |     1.576 |
-#> |.....................|   0.02295 |    0.7335 |     1.155 |     1.288 |
-#> |    X|     304.99974 |     94.15 |    0.8526 |     8.633 |     1.576 |
-#> |.....................|   0.02295 |    0.7335 |     1.155 |     1.288 |
-#> |    F| Forward Diff. |     30.20 |    0.6130 |     1.265 |    -28.57 |
-#> |.....................|    -3.511 |  -0.04200 |    -3.403 |    -5.652 |
-#> |   51|     304.64794 |     1.007 |    -1.040 |    -1.028 |  -0.08217 |
-#> |.....................|    -1.185 |   -0.9783 |   -0.8678 |   -0.7682 |
-#> |    U|     304.64794 |     93.75 |   -0.1607 |     2.153 |     1.584 |
-#> |.....................|   0.02273 |    0.7297 |     1.157 |     1.293 |
-#> |    X|     304.64794 |     93.75 |    0.8516 |     8.614 |     1.584 |
-#> |.....................|   0.02273 |    0.7297 |     1.157 |     1.293 |
-#> |    F| Forward Diff. |    -30.08 |    0.5385 |    0.9408 |    -28.96 |
-#> |.....................|    -3.779 |   -0.3908 |    -3.281 |    -5.515 |
-#> |   52|     304.28931 |     1.011 |    -1.041 |    -1.030 |  -0.06828 |
-#> |.....................|    -1.203 |   -0.9811 |   -0.8668 |   -0.7655 |
-#> |    U|     304.28931 |     94.14 |   -0.1618 |     2.151 |     1.591 |
-#> |.....................|   0.02250 |    0.7277 |     1.158 |     1.296 |
-#> |    X|     304.28931 |     94.14 |    0.8506 |     8.597 |     1.591 |
-#> |.....................|   0.02250 |    0.7277 |     1.158 |     1.296 |
-#> |   53|     304.03244 |     1.011 |    -1.042 |    -1.033 |  -0.05709 |
-#> |.....................|    -1.225 |   -0.9843 |   -0.8662 |   -0.7633 |
-#> |    U|     304.03244 |     94.13 |   -0.1630 |     2.149 |     1.597 |
-#> |.....................|   0.02223 |    0.7253 |     1.159 |     1.298 |
-#> |    X|     304.03244 |     94.13 |    0.8496 |     8.578 |     1.597 |
-#> |.....................|   0.02223 |    0.7253 |     1.159 |     1.298 |
-#> |   54|     302.98899 |     1.011 |    -1.047 |    -1.041 |  -0.01055 |
-#> |.....................|    -1.314 |   -0.9977 |   -0.8638 |   -0.7544 |
-#> |    U|     302.98899 |     94.10 |   -0.1678 |     2.140 |     1.623 |
-#> |.....................|   0.02111 |    0.7156 |     1.161 |     1.308 |
-#> |    X|     302.98899 |     94.10 |    0.8455 |     8.503 |     1.623 |
-#> |.....................|   0.02111 |    0.7156 |     1.161 |     1.308 |
-#> |   55|     298.89653 |     1.010 |    -1.068 |    -1.080 |    0.1944 |
-#> |.....................|    -1.708 |    -1.057 |   -0.8531 |   -0.7150 |
-#> |    U|     298.89653 |     93.99 |   -0.1892 |     2.101 |     1.735 |
-#> |.....................|   0.01618 |    0.6726 |     1.173 |     1.350 |
-#> |    X|     298.89653 |     93.99 |    0.8276 |     8.177 |     1.735 |
-#> |.....................|   0.01618 |    0.6726 |     1.173 |     1.350 |
-#> |   56|     292.24425 |     1.012 |    -1.205 |    -1.331 |     1.218 |
-#> |.....................|    -2.997 |    -1.313 |   -0.8095 |   -0.4981 |
-#> |    U|     292.24425 |     94.21 |   -0.3257 |     1.851 |     2.296 |
-#> |.....................| 5.960e-07 |    0.4863 |     1.218 |     1.582 |
-#> |    X|     292.24425 |     94.21 |    0.7221 |     6.365 |     2.296 |
-#> |.....................| 5.960e-07 |    0.4863 |     1.218 |     1.582 |
-#> |    F| Forward Diff. |    -17.20 |    -1.896 |    -10.23 |    0.3663 |
-#> |.....................|  0.002021 |    -17.85 |    0.1528 |     5.292 |
-#> |   57|     309.71599 |    0.9897 |    -1.187 |   -0.4357 |     2.442 |
-#> |.....................|    -2.997 |    0.5394 |   -0.6812 |   -0.7129 |
-#> |    U|     309.71599 |     92.14 |   -0.3076 |     2.746 |     2.966 |
-#> |.....................| 5.960e-07 |     1.833 |     1.352 |     1.352 |
-#> |    X|     309.71599 |     92.14 |    0.7352 |     15.58 |     2.966 |
-#> |.....................| 5.960e-07 |     1.833 |     1.352 |     1.352 |
-#> |   58|     292.01474 |     1.005 |    -1.198 |    -1.013 |     1.651 |
-#> |.....................|    -2.997 |   -0.6561 |   -0.7641 |   -0.5745 |
-#> |    U|     292.01474 |     93.60 |   -0.3191 |     2.168 |     2.533 |
-#> |.....................| 5.960e-07 |    0.9640 |     1.266 |     1.501 |
-#> |    X|     292.01474 |     93.60 |    0.7268 |     8.745 |     2.533 |
-#> |.....................| 5.960e-07 |    0.9640 |     1.266 |     1.501 |
-#> |    F| Forward Diff. |    -172.4 |    -2.986 |     3.411 |     4.977 |
-#> |.....................|   0.05585 |     3.841 |     3.028 |    0.3322 |
-#> |   59|     292.30890 |     1.013 |   -0.8632 |    -1.158 |     1.672 |
-#> |.....................|    -2.997 |   -0.5770 |   -0.9665 |   -0.6082 |
-#> |    U|      292.3089 |     94.28 |   0.01586 |     2.024 |     2.544 |
-#> |.....................| 5.960e-07 |     1.022 |     1.054 |     1.464 |
-#> |    X|      292.3089 |     94.28 |     1.016 |     7.565 |     2.544 |
-#> |.....................| 5.960e-07 |     1.022 |     1.054 |     1.464 |
-#> |   60|     291.20170 |     1.015 |    -1.046 |    -1.079 |     1.660 |
-#> |.....................|    -2.997 |   -0.6203 |   -0.8561 |   -0.5898 |
-#> |    U|      291.2017 |     94.51 |   -0.1669 |     2.103 |     2.538 |
-#> |.....................| 5.960e-07 |    0.9900 |     1.170 |     1.484 |
-#> |    X|      291.2017 |     94.51 |    0.8462 |     8.187 |     2.538 |
-#> |.....................| 5.960e-07 |    0.9900 |     1.170 |     1.484 |
-#> |    F| Forward Diff. |     39.51 |    0.9033 |     2.112 |     5.106 |
-#> |.....................|   0.03418 |     2.863 |    -2.696 |   -0.7695 |
-#> |   61|     291.43833 |     1.017 |    -1.033 |    -1.136 |     1.600 |
-#> |.....................|    -2.997 |   -0.6066 |   -0.6851 |   -0.5537 |
-#> |    U|     291.43833 |     94.73 |   -0.1542 |     2.046 |     2.505 |
-#> |.....................| 5.960e-07 |     1.000 |     1.348 |     1.523 |
-#> |    X|     291.43833 |     94.73 |    0.8571 |     7.739 |     2.505 |
-#> |.....................| 5.960e-07 |     1.000 |     1.348 |     1.523 |
-#> |   62|     290.99248 |     1.014 |    -1.041 |    -1.101 |     1.637 |
-#> |.....................|    -2.997 |   -0.6152 |   -0.7907 |   -0.5760 |
-#> |    U|     290.99248 |     94.43 |   -0.1621 |     2.081 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9938 |     1.238 |     1.499 |
-#> |    X|     290.99248 |     94.43 |    0.8503 |     8.012 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9938 |     1.238 |     1.499 |
-#> |    F| Forward Diff. |     14.98 |     1.278 |     1.101 |     4.858 |
-#> |.....................|   0.03639 |     3.021 |    0.9673 |   -0.2780 |
-#> |   63|     291.02454 |     1.009 |    -1.102 |    -1.088 |     1.608 |
-#> |.....................|    -2.997 |   -0.6330 |   -0.7900 |   -0.5542 |
-#> |    U|     291.02454 |     93.95 |   -0.2228 |     2.094 |     2.510 |
-#> |.....................| 5.960e-07 |    0.9808 |     1.239 |     1.522 |
-#> |    X|     291.02454 |     93.95 |    0.8003 |     8.118 |     2.510 |
-#> |.....................| 5.960e-07 |    0.9808 |     1.239 |     1.522 |
-#> |   64|     291.12722 |     1.009 |    -1.068 |    -1.095 |     1.623 |
-#> |.....................|    -2.997 |   -0.6237 |   -0.7906 |   -0.5663 |
-#> |    U|     291.12722 |     93.94 |   -0.1892 |     2.087 |     2.518 |
-#> |.....................| 5.960e-07 |    0.9876 |     1.238 |     1.509 |
-#> |    X|     291.12722 |     93.94 |    0.8276 |     8.057 |     2.518 |
-#> |.....................| 5.960e-07 |    0.9876 |     1.238 |     1.509 |
-#> |   65|     291.20836 |     1.009 |    -1.048 |    -1.100 |     1.633 |
-#> |.....................|    -2.997 |   -0.6180 |   -0.7910 |   -0.5738 |
-#> |    U|     291.20836 |     93.93 |   -0.1686 |     2.082 |     2.523 |
-#> |.....................| 5.960e-07 |    0.9918 |     1.238 |     1.501 |
-#> |    X|     291.20836 |     93.93 |    0.8449 |     8.020 |     2.523 |
-#> |.....................| 5.960e-07 |    0.9918 |     1.238 |     1.501 |
-#> |   66|     290.99661 |     1.013 |    -1.041 |    -1.101 |     1.637 |
-#> |.....................|    -2.997 |   -0.6156 |   -0.7909 |   -0.5760 |
-#> |    U|     290.99661 |     94.27 |   -0.1623 |     2.081 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9935 |     1.238 |     1.499 |
-#> |    X|     290.99661 |     94.27 |    0.8502 |     8.011 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9935 |     1.238 |     1.499 |
-#> |   67|     290.98636 |     1.014 |    -1.041 |    -1.101 |     1.637 |
-#> |.....................|    -2.997 |   -0.6154 |   -0.7908 |   -0.5760 |
-#> |    U|     290.98636 |     94.36 |   -0.1622 |     2.081 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9936 |     1.238 |     1.499 |
-#> |    X|     290.98636 |     94.36 |    0.8503 |     8.012 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9936 |     1.238 |     1.499 |
-#> |    F| Forward Diff. |    -1.956 |     1.256 |    0.9523 |     4.835 |
-#> |.....................|   0.03649 |     3.031 |    0.9657 |   -0.2695 |
-#> |   68|     290.98211 |     1.014 |    -1.041 |    -1.101 |     1.636 |
-#> |.....................|    -2.997 |   -0.6157 |   -0.7909 |   -0.5760 |
-#> |    U|     290.98211 |     94.38 |   -0.1623 |     2.081 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9934 |     1.238 |     1.499 |
-#> |    X|     290.98211 |     94.38 |    0.8502 |     8.011 |     2.525 |
-#> |.....................| 5.960e-07 |    0.9934 |     1.238 |     1.499 |
-#> |   69|     290.97746 |     1.014 |    -1.042 |    -1.101 |     1.635 |
-#> |.....................|    -2.997 |   -0.6167 |   -0.7912 |   -0.5759 |
-#> |    U|     290.97746 |     94.44 |   -0.1627 |     2.081 |     2.524 |
-#> |.....................| 5.960e-07 |    0.9927 |     1.237 |     1.499 |
-#> |    X|     290.97746 |     94.44 |    0.8498 |     8.009 |     2.524 |
-#> |.....................| 5.960e-07 |    0.9927 |     1.237 |     1.499 |
-#> |    F| Forward Diff. |     17.70 |     1.268 |     1.108 |     4.855 |
-#> |.....................|   0.04257 |     3.066 |    0.9427 |   -0.2771 |
-#> |   70|     290.96180 |     1.014 |    -1.044 |    -1.101 |     1.634 |
-#> |.....................|    -2.997 |   -0.6175 |   -0.7910 |   -0.5752 |
-#> |    U|      290.9618 |     94.36 |   -0.1647 |     2.081 |     2.523 |
-#> |.....................| 5.960e-07 |    0.9921 |     1.238 |     1.500 |
-#> |    X|      290.9618 |     94.36 |    0.8481 |     8.013 |     2.523 |
-#> |.....................| 5.960e-07 |    0.9921 |     1.238 |     1.500 |
-#> |    F| Forward Diff. |    -1.598 |     1.197 |    0.9704 |     4.824 |
-#> |.....................|   0.03731 |     2.941 |    0.9551 |   -0.2334 |
-#> |   71|     290.95083 |     1.014 |    -1.044 |    -1.101 |     1.632 |
-#> |.....................|    -2.997 |   -0.6188 |   -0.7915 |   -0.5751 |
-#> |    U|     290.95083 |     94.43 |   -0.1653 |     2.081 |     2.522 |
-#> |.....................| 5.960e-07 |    0.9912 |     1.237 |     1.500 |
-#> |    X|     290.95083 |     94.43 |    0.8477 |     8.010 |     2.522 |
-#> |.....................| 5.960e-07 |    0.9912 |     1.237 |     1.500 |
-#> |    F| Forward Diff. |     14.81 |     1.204 |     1.097 |     4.820 |
-#> |.....................|   0.03908 |     3.014 |    0.9116 |   -0.2462 |
-#> |   72|     290.93714 |     1.014 |    -1.046 |    -1.101 |     1.630 |
-#> |.....................|    -2.997 |   -0.6196 |   -0.7913 |   -0.5744 |
-#> |    U|     290.93714 |     94.36 |   -0.1673 |     2.081 |     2.522 |
-#> |.....................| 5.960e-07 |    0.9906 |     1.237 |     1.501 |
-#> |    X|     290.93714 |     94.36 |    0.8459 |     8.014 |     2.522 |
-#> |.....................| 5.960e-07 |    0.9906 |     1.237 |     1.501 |
-#> |    F| Forward Diff. |    -1.943 |     1.135 |    0.9791 |     4.793 |
-#> |.....................|   0.03360 |     3.051 |    0.9080 |   -0.2200 |
-#> |   73|     290.92845 |     1.014 |    -1.047 |    -1.101 |     1.628 |
-#> |.....................|    -2.997 |   -0.6209 |   -0.7917 |   -0.5743 |
-#> |    U|     290.92845 |     94.44 |   -0.1678 |     2.081 |     2.521 |
-#> |.....................| 5.960e-07 |    0.9896 |     1.237 |     1.501 |
-#> |    X|     290.92845 |     94.44 |    0.8455 |     8.011 |     2.521 |
-#> |.....................| 5.960e-07 |    0.9896 |     1.237 |     1.501 |
-#> |    F| Forward Diff. |     17.70 |     1.147 |     1.134 |     4.752 |
-#> |.....................|   0.02729 |     3.018 |    0.8867 |   -0.2229 |
-#> |   74|     290.91300 |     1.014 |    -1.049 |    -1.100 |     1.627 |
-#> |.....................|    -2.997 |   -0.6219 |   -0.7915 |   -0.5737 |
-#> |    U|       290.913 |     94.36 |   -0.1698 |     2.081 |     2.520 |
-#> |.....................| 5.960e-07 |    0.9889 |     1.237 |     1.501 |
-#> |    X|       290.913 |     94.36 |    0.8439 |     8.016 |     2.520 |
-#> |.....................| 5.960e-07 |    0.9889 |     1.237 |     1.501 |
-#> |    F| Forward Diff. |    -1.940 |     1.078 |    0.9981 |     4.722 |
-#> |.....................|   0.04064 |     3.105 |    0.9143 |   -0.1849 |
-#> |   75|     290.90444 |     1.014 |    -1.049 |    -1.101 |     1.625 |
-#> |.....................|    -2.997 |   -0.6232 |   -0.7919 |   -0.5736 |
-#> |    U|     290.90444 |     94.44 |   -0.1702 |     2.081 |     2.519 |
-#> |.....................| 5.960e-07 |    0.9879 |     1.237 |     1.501 |
-#> |    X|     290.90444 |     94.44 |    0.8435 |     8.013 |     2.519 |
-#> |.....................| 5.960e-07 |    0.9879 |     1.237 |     1.501 |
-#> |    F| Forward Diff. |     17.76 |     1.091 |     1.153 |     4.713 |
-#> |.....................|   0.03198 |     2.950 |    0.8627 |   -0.2001 |
-#> |   76|     290.88905 |     1.014 |    -1.051 |    -1.100 |     1.624 |
-#> |.....................|    -2.997 |   -0.6243 |   -0.7916 |   -0.5732 |
-#> |    U|     290.88905 |     94.36 |   -0.1722 |     2.082 |     2.518 |
-#> |.....................| 5.960e-07 |    0.9872 |     1.237 |     1.502 |
-#> |    X|     290.88905 |     94.36 |    0.8418 |     8.019 |     2.518 |
-#> |.....................| 5.960e-07 |    0.9872 |     1.237 |     1.502 |
-#> |    F| Forward Diff. |    -2.112 |     1.022 |     1.016 |     4.749 |
-#> |.....................|   0.03990 |     3.117 |    0.8810 |   -0.1779 |
-#> |   77|     290.87937 |     1.014 |    -1.052 |    -1.100 |     1.622 |
-#> |.....................|    -2.997 |   -0.6257 |   -0.7918 |   -0.5730 |
-#> |    U|     290.87937 |     94.43 |   -0.1731 |     2.082 |     2.517 |
-#> |.....................| 5.960e-07 |    0.9861 |     1.237 |     1.502 |
-#> |    X|     290.87937 |     94.43 |    0.8411 |     8.018 |     2.517 |
-#> |.....................| 5.960e-07 |    0.9861 |     1.237 |     1.502 |
-#> |    F| Forward Diff. |     15.72 |     1.022 |     1.168 |     4.728 |
-#> |.....................|   0.04036 |     3.118 |    0.8621 |   -0.1806 |
-#> |   78|     290.86528 |     1.014 |    -1.054 |    -1.099 |     1.621 |
-#> |.....................|    -2.997 |   -0.6269 |   -0.7915 |   -0.5727 |
-#> |    U|     290.86528 |     94.36 |   -0.1749 |     2.083 |     2.516 |
-#> |.....................| 5.960e-07 |    0.9853 |     1.237 |     1.502 |
-#> |    X|     290.86528 |     94.36 |    0.8396 |     8.025 |     2.516 |
-#> |.....................| 5.960e-07 |    0.9853 |     1.237 |     1.502 |
-#> |    F| Forward Diff. |    -2.089 |    0.9583 |     1.055 |     4.711 |
-#> |.....................|   0.04161 |     3.089 |    0.8790 |   -0.1555 |
-#> |   79|     290.85625 |     1.014 |    -1.055 |    -1.099 |     1.619 |
-#> |.....................|    -2.997 |   -0.6283 |   -0.7918 |   -0.5726 |
-#> |    U|     290.85625 |     94.44 |   -0.1756 |     2.082 |     2.515 |
-#> |.....................| 5.960e-07 |    0.9842 |     1.237 |     1.503 |
-#> |    X|     290.85625 |     94.44 |    0.8389 |     8.023 |     2.515 |
-#> |.....................| 5.960e-07 |    0.9842 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |     16.77 |    0.9641 |     1.212 |     4.706 |
-#> |.....................|   0.04215 |     3.138 |    0.8554 |   -0.1643 |
-#> |   80|     290.84140 |     1.014 |    -1.056 |    -1.099 |     1.618 |
-#> |.....................|    -2.997 |   -0.6296 |   -0.7915 |   -0.5724 |
-#> |    U|      290.8414 |     94.36 |   -0.1774 |     2.083 |     2.515 |
-#> |.....................| 5.960e-07 |    0.9833 |     1.237 |     1.503 |
-#> |    X|      290.8414 |     94.36 |    0.8375 |     8.030 |     2.515 |
-#> |.....................| 5.960e-07 |    0.9833 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |    -1.641 |    0.9006 |     1.093 |     4.694 |
-#> |.....................|   0.04205 |     3.147 |    0.8775 |   -0.1452 |
-#> |   81|     290.83107 |     1.014 |    -1.057 |    -1.099 |     1.616 |
-#> |.....................|    -2.997 |   -0.6310 |   -0.7919 |   -0.5723 |
-#> |    U|     290.83107 |     94.43 |   -0.1778 |     2.083 |     2.514 |
-#> |.....................| 5.960e-07 |    0.9823 |     1.237 |     1.503 |
-#> |    X|     290.83107 |     94.43 |    0.8371 |     8.026 |     2.514 |
-#> |.....................| 5.960e-07 |    0.9823 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |     15.22 |    0.9116 |     1.221 |     4.655 |
-#> |.....................|   0.04015 |     3.140 |    0.8393 |   -0.1501 |
-#> |   82|     290.81725 |     1.014 |    -1.059 |    -1.098 |     1.615 |
-#> |.....................|    -2.997 |   -0.6323 |   -0.7916 |   -0.5722 |
-#> |    U|     290.81725 |     94.36 |   -0.1795 |     2.084 |     2.513 |
-#> |.....................| 5.960e-07 |    0.9813 |     1.237 |     1.503 |
-#> |    X|     290.81725 |     94.36 |    0.8357 |     8.034 |     2.513 |
-#> |.....................| 5.960e-07 |    0.9813 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |    -2.105 |    0.8517 |     1.114 |     4.660 |
-#> |.....................|   0.03878 |     3.162 |    0.8666 |   -0.1313 |
-#> |   83|     290.80795 |     1.014 |    -1.059 |    -1.098 |     1.613 |
-#> |.....................|    -2.997 |   -0.6339 |   -0.7918 |   -0.5722 |
-#> |    U|     290.80795 |     94.43 |   -0.1802 |     2.084 |     2.512 |
-#> |.....................| 5.960e-07 |    0.9802 |     1.237 |     1.503 |
-#> |    X|     290.80795 |     94.43 |    0.8351 |     8.033 |     2.512 |
-#> |.....................| 5.960e-07 |    0.9802 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |     16.11 |    0.8564 |     1.267 |     4.653 |
-#> |.....................|   0.04303 |     3.178 |    0.8469 |   -0.1413 |
-#> |   84|     290.79348 |     1.014 |    -1.061 |    -1.097 |     1.611 |
-#> |.....................|    -2.997 |   -0.6353 |   -0.7914 |   -0.5722 |
-#> |    U|     290.79348 |     94.36 |   -0.1817 |     2.084 |     2.511 |
-#> |.....................| 5.960e-07 |    0.9792 |     1.237 |     1.503 |
-#> |    X|     290.79348 |     94.36 |    0.8338 |     8.041 |     2.511 |
-#> |.....................| 5.960e-07 |    0.9792 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |    -1.840 |    0.7976 |     1.155 |     4.587 |
-#> |.....................|   0.02723 |     3.115 |    0.8603 |   -0.1275 |
-#> |   85|     290.78474 |     1.014 |    -1.061 |    -1.098 |     1.609 |
-#> |.....................|    -2.997 |   -0.6367 |   -0.7918 |   -0.5721 |
-#> |    U|     290.78474 |     94.44 |   -0.1821 |     2.084 |     2.510 |
-#> |.....................| 5.960e-07 |    0.9781 |     1.237 |     1.503 |
-#> |    X|     290.78474 |     94.44 |    0.8335 |     8.036 |     2.510 |
-#> |.....................| 5.960e-07 |    0.9781 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |     17.19 |    0.8130 |     1.300 |     4.618 |
-#> |.....................|   0.03919 |     3.190 |    0.8345 |   -0.1328 |
-#> |   86|     290.76934 |     1.014 |    -1.063 |    -1.097 |     1.608 |
-#> |.....................|    -2.997 |   -0.6382 |   -0.7915 |   -0.5722 |
-#> |    U|     290.76934 |     94.36 |   -0.1836 |     2.085 |     2.510 |
-#> |.....................| 5.960e-07 |    0.9771 |     1.237 |     1.503 |
-#> |    X|     290.76934 |     94.36 |    0.8322 |     8.044 |     2.510 |
-#> |.....................| 5.960e-07 |    0.9771 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |    -1.203 |    0.7543 |     1.182 |     4.565 |
-#> |.....................|   0.03490 |     3.166 |    0.8589 |   -0.1256 |
-#> |   87|     290.75687 |     1.014 |    -1.063 |    -1.097 |     1.606 |
-#> |.....................|    -2.997 |   -0.6397 |   -0.7919 |   -0.5722 |
-#> |    U|     290.75687 |     94.41 |   -0.1840 |     2.084 |     2.508 |
-#> |.....................| 5.960e-07 |    0.9760 |     1.237 |     1.503 |
-#> |    X|     290.75687 |     94.41 |    0.8319 |     8.039 |     2.508 |
-#> |.....................| 5.960e-07 |    0.9760 |     1.237 |     1.503 |
-#> |   88|     290.75123 |     1.015 |    -1.063 |    -1.098 |     1.604 |
-#> |.....................|    -2.997 |   -0.6414 |   -0.7924 |   -0.5721 |
-#> |    U|     290.75123 |     94.47 |   -0.1844 |     2.084 |     2.507 |
-#> |.....................| 5.960e-07 |    0.9747 |     1.236 |     1.503 |
-#> |    X|     290.75123 |     94.47 |    0.8316 |     8.034 |     2.507 |
-#> |.....................| 5.960e-07 |    0.9747 |     1.236 |     1.503 |
-#> |    F| Forward Diff. |     26.23 |    0.7709 |     1.374 |     4.560 |
-#> |.....................|   0.04194 |     3.213 |    0.7966 |   -0.1353 |
-#> |   89|     290.71744 |     1.014 |    -1.067 |    -1.096 |     1.601 |
-#> |.....................|    -2.997 |   -0.6448 |   -0.7915 |   -0.5726 |
-#> |    U|     290.71744 |     94.37 |   -0.1875 |     2.086 |     2.506 |
-#> |.....................| 5.960e-07 |    0.9722 |     1.237 |     1.503 |
-#> |    X|     290.71744 |     94.37 |    0.8291 |     8.054 |     2.506 |
-#> |.....................| 5.960e-07 |    0.9722 |     1.237 |     1.503 |
-#> |    F| Forward Diff. |    0.1928 |    0.6670 |     1.256 |     4.555 |
-#> |.....................|   0.04212 |     3.227 |    0.8436 |   -0.1302 |
-#> |   90|     290.68496 |     1.013 |    -1.067 |    -1.097 |     1.597 |
-#> |.....................|    -2.997 |   -0.6481 |   -0.7924 |   -0.5725 |
-#> |    U|     290.68496 |     94.35 |   -0.1881 |     2.085 |     2.503 |
-#> |.....................| 5.960e-07 |    0.9698 |     1.236 |     1.503 |
-#> |    X|     290.68496 |     94.35 |    0.8285 |     8.044 |     2.503 |
-#> |.....................| 5.960e-07 |    0.9698 |     1.236 |     1.503 |
-#> |   91|     290.59496 |     1.013 |    -1.069 |    -1.101 |     1.583 |
-#> |.....................|    -2.997 |   -0.6580 |   -0.7950 |   -0.5721 |
-#> |    U|     290.59496 |     94.29 |   -0.1902 |     2.081 |     2.496 |
-#> |.....................| 5.960e-07 |    0.9627 |     1.233 |     1.503 |
-#> |    X|     290.59496 |     94.29 |    0.8268 |     8.013 |     2.496 |
-#> |.....................| 5.960e-07 |    0.9627 |     1.233 |     1.503 |
-#> |   92|     290.34408 |     1.010 |    -1.077 |    -1.116 |     1.527 |
-#> |.....................|    -2.997 |   -0.6974 |   -0.8053 |   -0.5705 |
-#> |    U|     290.34408 |     94.08 |   -0.1983 |     2.066 |     2.465 |
-#> |.....................| 5.960e-07 |    0.9340 |     1.223 |     1.505 |
-#> |    X|     290.34408 |     94.08 |    0.8201 |     7.891 |     2.465 |
-#> |.....................| 5.960e-07 |    0.9340 |     1.223 |     1.505 |
-#> |    F| Forward Diff. |    -74.08 |    0.3588 |   -0.1794 |     3.803 |
-#> |.....................|   0.04205 |     3.779 |   0.06785 | -0.005437 |
-#> |   93|     289.95778 |     1.012 |    -1.081 |    -1.068 |     1.490 |
-#> |.....................|    -2.997 |   -0.7670 |   -0.7909 |   -0.5845 |
-#> |    U|     289.95778 |     94.18 |   -0.2020 |     2.114 |     2.445 |
-#> |.....................| 5.960e-07 |    0.8834 |     1.238 |     1.490 |
-#> |    X|     289.95778 |     94.18 |    0.8171 |     8.282 |     2.445 |
-#> |.....................| 5.960e-07 |    0.8834 |     1.238 |     1.490 |
-#> |   94|     289.83089 |     1.009 |    -1.086 |    -1.006 |     1.442 |
-#> |.....................|    -2.997 |   -0.8563 |   -0.7725 |   -0.6025 |
-#> |    U|     289.83089 |     93.98 |   -0.2067 |     2.176 |     2.418 |
-#> |.....................| 5.960e-07 |    0.8185 |     1.257 |     1.470 |
-#> |    X|     289.83089 |     93.98 |    0.8132 |     8.812 |     2.418 |
-#> |.....................| 5.960e-07 |    0.8185 |     1.257 |     1.470 |
-#> |    F| Forward Diff. |    -65.01 |  -0.01626 |     4.198 |     3.297 |
-#> |.....................|   0.05097 |     3.562 |     1.909 |   -0.3175 |
-#> |   95|     290.63229 |     1.014 |    -1.226 |    -1.068 |     1.287 |
-#> |.....................|    -2.997 |    -1.101 |   -0.7595 |   -0.8853 |
-#> |    U|     290.63229 |     94.43 |   -0.3467 |     2.113 |     2.333 |
-#> |.....................| 5.960e-07 |    0.6407 |     1.271 |     1.167 |
-#> |    X|     290.63229 |     94.43 |    0.7070 |     8.277 |     2.333 |
-#> |.....................| 5.960e-07 |    0.6407 |     1.271 |     1.167 |
-#> |   96|     289.56584 |     1.017 |    -1.134 |    -1.028 |     1.388 |
-#> |.....................|    -2.997 |   -0.9416 |   -0.7681 |   -0.7007 |
-#> |    U|     289.56584 |     94.70 |   -0.2554 |     2.154 |     2.389 |
-#> |.....................| 5.960e-07 |    0.7564 |     1.261 |     1.365 |
-#> |    X|     289.56584 |     94.70 |    0.7746 |     8.619 |     2.389 |
-#> |.....................| 5.960e-07 |    0.7564 |     1.261 |     1.365 |
-#> |    F| Forward Diff. |     59.80 |   -0.9076 |     3.450 |     2.884 |
-#> |.....................|   0.04168 |     2.247 |     1.868 |    -3.338 |
-#> |   97|     289.16078 |     1.017 |    -1.094 |    -1.010 |     1.317 |
-#> |.....................|    -2.997 |   -0.9798 |   -0.7948 |   -0.5837 |
-#> |    U|     289.16078 |     94.64 |   -0.2152 |     2.172 |     2.350 |
-#> |.....................| 5.960e-07 |    0.7287 |     1.234 |     1.491 |
-#> |    X|     289.16078 |     94.64 |    0.8063 |     8.773 |     2.350 |
-#> |.....................| 5.960e-07 |    0.7287 |     1.234 |     1.491 |
-#> |    F| Forward Diff. |     50.77 |  -0.08196 |     5.132 |     1.948 |
-#> |.....................|   0.04608 |     1.474 |    0.6389 |    0.4459 |
-#> |   98|     290.19527 |     1.002 |    -1.018 |    -1.037 |     1.157 |
-#> |.....................|    -2.997 |    -1.195 |   -0.7989 |   -0.6967 |
-#> |    U|     290.19527 |     93.32 |   -0.1385 |     2.145 |     2.263 |
-#> |.....................| 5.960e-07 |    0.5724 |     1.229 |     1.370 |
-#> |    X|     290.19527 |     93.32 |    0.8707 |     8.542 |     2.263 |
-#> |.....................| 5.960e-07 |    0.5724 |     1.229 |     1.370 |
-#> |   99|     289.65582 |     1.003 |    -1.072 |    -1.019 |     1.270 |
-#> |.....................|    -2.997 |    -1.043 |   -0.7961 |   -0.6170 |
-#> |    U|     289.65582 |     93.34 |   -0.1926 |     2.163 |     2.324 |
-#> |.....................| 5.960e-07 |    0.6825 |     1.232 |     1.455 |
-#> |    X|     289.65582 |     93.34 |    0.8248 |     8.696 |     2.324 |
-#> |.....................| 5.960e-07 |    0.6825 |     1.232 |     1.455 |
-#> |  100|     289.77865 |     1.003 |    -1.088 |    -1.014 |     1.303 |
-#> |.....................|    -2.997 |   -0.9984 |   -0.7953 |   -0.5934 |
-#> |    U|     289.77865 |     93.35 |   -0.2087 |     2.168 |     2.342 |
-#> |.....................| 5.960e-07 |    0.7151 |     1.233 |     1.480 |
-#> |    X|     289.77865 |     93.35 |    0.8116 |     8.742 |     2.342 |
-#> |.....................| 5.960e-07 |    0.7151 |     1.233 |     1.480 |
-#> |  101|     289.23886 |     1.008 |    -1.094 |    -1.011 |     1.317 |
-#> |.....................|    -2.997 |   -0.9800 |   -0.7949 |   -0.5837 |
-#> |    U|     289.23886 |     93.87 |   -0.2152 |     2.171 |     2.350 |
-#> |.....................| 5.960e-07 |    0.7285 |     1.234 |     1.491 |
-#> |    X|     289.23886 |     93.87 |    0.8064 |     8.765 |     2.350 |
-#> |.....................| 5.960e-07 |    0.7285 |     1.234 |     1.491 |
-#> |  102|     289.07165 |     1.013 |    -1.094 |    -1.010 |     1.317 |
-#> |.....................|    -2.997 |   -0.9799 |   -0.7948 |   -0.5837 |
-#> |    U|     289.07165 |     94.31 |   -0.2152 |     2.171 |     2.350 |
-#> |.....................| 5.960e-07 |    0.7286 |     1.234 |     1.491 |
-#> |    X|     289.07165 |     94.31 |    0.8063 |     8.770 |     2.350 |
-#> |.....................| 5.960e-07 |    0.7286 |     1.234 |     1.491 |
-#> |    F| Forward Diff. |   -0.3607 |   -0.1394 |     4.728 |     1.937 |
-#> |.....................|   0.04518 |     1.333 |    0.6601 |    0.3686 |
-#> |  103|     289.05383 |     1.013 |    -1.094 |    -1.014 |     1.315 |
-#> |.....................|    -2.997 |   -0.9807 |   -0.7952 |   -0.5839 |
-#> |    U|     289.05383 |     94.33 |   -0.2152 |     2.168 |     2.349 |
-#> |.....................| 5.960e-07 |    0.7280 |     1.233 |     1.490 |
-#> |    X|     289.05383 |     94.33 |    0.8064 |     8.742 |     2.349 |
-#> |.....................| 5.960e-07 |    0.7280 |     1.233 |     1.490 |
-#> |  104|     289.00706 |     1.014 |    -1.094 |    -1.023 |     1.312 |
-#> |.....................|    -2.997 |   -0.9834 |   -0.7965 |   -0.5847 |
-#> |    U|     289.00706 |     94.40 |   -0.2149 |     2.159 |     2.347 |
-#> |.....................| 5.960e-07 |    0.7260 |     1.232 |     1.490 |
-#> |    X|     289.00706 |     94.40 |    0.8066 |     8.661 |     2.347 |
-#> |.....................| 5.960e-07 |    0.7260 |     1.232 |     1.490 |
-#> |  105|     288.92149 |     1.016 |    -1.093 |    -1.055 |     1.299 |
-#> |.....................|    -2.997 |   -0.9924 |   -0.8010 |   -0.5872 |
-#> |    U|     288.92149 |     94.63 |   -0.2139 |     2.127 |     2.340 |
-#> |.....................| 5.960e-07 |    0.7195 |     1.227 |     1.487 |
-#> |    X|     288.92149 |     94.63 |    0.8074 |     8.388 |     2.340 |
-#> |.....................| 5.960e-07 |    0.7195 |     1.227 |     1.487 |
-#> |    F| Forward Diff. |     43.21 |   0.03028 |     3.221 |     1.557 |
-#> |.....................|  0.008151 |     1.175 |    0.2057 |   -0.1154 |
-#> |  106|     288.79118 |     1.014 |    -1.096 |    -1.061 |     1.264 |
-#> |.....................|    -2.997 |    -1.027 |   -0.7973 |   -0.5956 |
-#> |    U|     288.79118 |     94.43 |   -0.2174 |     2.120 |     2.321 |
-#> |.....................| 5.960e-07 |    0.6943 |     1.231 |     1.478 |
-#> |    X|     288.79118 |     94.43 |    0.8046 |     8.334 |     2.321 |
-#> |.....................| 5.960e-07 |    0.6943 |     1.231 |     1.478 |
-#> |    F| Forward Diff. |     10.81 |  -0.06252 |     2.679 |     1.204 |
-#> |.....................|   0.03262 |   -0.1240 |    0.4322 |   -0.2470 |
-#> |  107|     288.75294 |     1.013 |    -1.132 |    -1.081 |     1.252 |
-#> |.....................|    -2.997 |    -1.011 |   -0.7930 |   -0.5741 |
-#> |    U|     288.75294 |     94.35 |   -0.2531 |     2.101 |     2.314 |
-#> |.....................| 5.960e-07 |    0.7060 |     1.235 |     1.501 |
-#> |    X|     288.75294 |     94.35 |    0.7764 |     8.173 |     2.314 |
-#> |.....................| 5.960e-07 |    0.7060 |     1.235 |     1.501 |
-#> |    F| Forward Diff. |    -3.091 |   -0.8602 |     1.971 |     1.009 |
-#> |.....................|   0.04475 |    0.5130 |    0.7746 |    0.2303 |
-#> |  108|     288.69834 |     1.013 |    -1.093 |    -1.104 |     1.232 |
-#> |.....................|    -2.997 |    -1.011 |   -0.7973 |   -0.5721 |
-#> |    U|     288.69834 |     94.27 |   -0.2136 |     2.078 |     2.303 |
-#> |.....................| 5.960e-07 |    0.7061 |     1.231 |     1.503 |
-#> |    X|     288.69834 |     94.27 |    0.8077 |     7.987 |     2.303 |
-#> |.....................| 5.960e-07 |    0.7061 |     1.231 |     1.503 |
-#> |    F| Forward Diff. |    -16.61 |   0.06814 |    0.8311 |    0.6184 |
-#> |.....................|   0.03151 |    0.5612 |    0.4558 |    0.3067 |
-#> |  109|     288.67099 |     1.014 |    -1.108 |    -1.122 |     1.197 |
-#> |.....................|    -2.997 |    -1.038 |   -0.8030 |   -0.5758 |
-#> |    U|     288.67099 |     94.36 |   -0.2285 |     2.060 |     2.284 |
-#> |.....................| 5.960e-07 |    0.6866 |     1.225 |     1.499 |
-#> |    X|     288.67099 |     94.36 |    0.7957 |     7.847 |     2.284 |
-#> |.....................| 5.960e-07 |    0.6866 |     1.225 |     1.499 |
-#> |    F| Forward Diff. |    -4.975 |   -0.2154 |    0.1983 |    0.1047 |
-#> |.....................|   0.03564 |   -0.4652 |    0.1266 |    0.2269 |
-#> |  110|     288.66432 |     1.014 |    -1.097 |    -1.128 |     1.196 |
-#> |.....................|    -2.997 |    -1.027 |   -0.8055 |   -0.5813 |
-#> |    U|     288.66432 |     94.40 |   -0.2184 |     2.053 |     2.283 |
-#> |.....................| 5.960e-07 |    0.6941 |     1.222 |     1.493 |
-#> |    X|     288.66432 |     94.40 |    0.8038 |     7.793 |     2.283 |
-#> |.....................| 5.960e-07 |    0.6941 |     1.222 |     1.493 |
-#> |    F| Forward Diff. |    0.3927 |   0.02780 |  -0.05986 |   0.04997 |
-#> |.....................|   0.03453 |  -0.01180 |  -0.03408 |   0.03556 |
-#> |  111|     288.66432 |     1.014 |    -1.097 |    -1.128 |     1.196 |
-#> |.....................|    -2.997 |    -1.027 |   -0.8055 |   -0.5813 |
-#> |    U|     288.66432 |     94.40 |   -0.2184 |     2.053 |     2.283 |
-#> |.....................| 5.960e-07 |    0.6941 |     1.222 |     1.493 |
-#> |    X|     288.66432 |     94.40 |    0.8038 |     7.793 |     2.283 |
-#> |.....................| 5.960e-07 |    0.6941 |     1.222 |     1.493 |
-#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: parameter estimate near boundary; covariance not calculated:
+f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem",
+  control = saemControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> Calculating covariance matrix
#> 
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → compiling EBE model...
#>  
#> ✔ done
#> Calculating residuals/tables
#> done
f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei",
+  control = foceiControl(print = 0))
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> done
#> Calculating residuals/tables
#> done
#> Warning: initial ETAs were nudged; (can control by foceiControl(etaNudge=., etaNudge2=))
#> Warning: ETAs were reset to zero during optimization; (Can control by foceiControl(resetEtaP=.))
#> Warning: last objective function was not at minimum, possible problems in optimization
#> Warning: parameter estimate near boundary; covariance not calculated:
 #>    "rsd_high" 
 #>  use 'getVarCov' to calculate anyway
#> Warning: gradient problems with initial estimate; see $scaleInfo

 AIC(
@@ -4440,9 +347,8 @@ obtained by fitting the same model to a list of datasets using AIC(nlme(f_mmkin_parent["FOMC", ]))
 
#> [1] 468.0781
AIC(nlme(f_mmkin_parent["HS", ]))
 
#> [1] 535.609

-# nlme is comparable to nlmixr with focei, saem finds a better
-# solution, the two-component error model does not improve it
-plot(f_nlmixr_fomc_saem)
+# The FOCEI fit of FOMC with constant variance or the tc error model is best
+plot(f_nlmixr_fomc_saem_tc)
 

 sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
   A1 = mkinsub("SFO"))
@@ -4503,7 +409,7 @@ obtained by fitting the same model to a list of datasets using k_A1=rx_expr_11;
 #> f_parent=1/(1+exp(-(ETA[4]+THETA[4])));
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.546 0.379 5.924
f_nlmixr_fomc_sfo_focei_const <- nlmixr(f_mmkin_const["FOMC-SFO", ], est = "focei")
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 5.549 0.41 5.959
f_nlmixr_fomc_sfo_focei_const <- nlmixr(f_mmkin_const["FOMC-SFO", ], est = "focei")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
 #> rx_expr_6~ETA[1]+THETA[1];
@@ -4552,7 +458,7 @@ obtained by fitting the same model to a list of datasets using beta=exp(rx_expr_8);
 #> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.842 0.338 7.177
f_nlmixr_dfop_sfo_focei_const <- nlmixr(f_mmkin_const["DFOP-SFO", ], est = "focei")
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.93 0.367 7.293
f_nlmixr_dfop_sfo_focei_const <- nlmixr(f_mmkin_const["DFOP-SFO", ], est = "focei")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
 #> rx_expr_6~ETA[1]+THETA[1];
@@ -4609,10 +515,10 @@ obtained by fitting the same model to a list of datasets using f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> g=1/(rx_expr_20);
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.14 0.971 16.13

+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 15.39 1.223 16.61

 # Variance by variable is supported by 'saem' and 'focei'
 f_nlmixr_fomc_sfo_saem_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "saem")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.271 0.123 1.393
f_nlmixr_fomc_sfo_focei_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "focei")
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.288 0.09 1.379
f_nlmixr_fomc_sfo_focei_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "focei")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
 #> rx_expr_6~ETA[1]+THETA[1];
@@ -4661,8 +567,8 @@ obtained by fitting the same model to a list of datasets using beta=exp(rx_expr_8);
 #> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.699 0.341 7.038
f_nlmixr_dfop_sfo_saem_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "saem")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.384 0.092 1.477
f_nlmixr_dfop_sfo_focei_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "focei")
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 6.666 0.38 7.044
f_nlmixr_dfop_sfo_saem_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "saem")
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> → generate SAEM model
#> ✔ done
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 1.39 0.093 1.483
f_nlmixr_dfop_sfo_focei_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "focei")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
 #> rx_expr_6~ETA[1]+THETA[1];
@@ -4719,7 +625,7 @@ obtained by fitting the same model to a list of datasets using f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> g=1/(rx_expr_19);
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 14.86 1.172 16.03

+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 14.67 0.529 15.2

 # Identical two-component error for all variables is only possible with
 # est = 'focei' in nlmixr
 f_nlmixr_fomc_sfo_focei_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei")
@@ -4773,7 +679,7 @@ obtained by fitting the same model to a list of datasets using beta=exp(rx_expr_8);
 #> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.461 0.404 8.863
f_nlmixr_dfop_sfo_focei_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei")
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.455 0.377 8.841
f_nlmixr_dfop_sfo_focei_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
 #> rx_expr_6~ETA[1]+THETA[1];
@@ -4832,12 +738,12 @@ obtained by fitting the same model to a list of datasets using f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> g=1/(rx_expr_21);
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 18.02 0.925 18.94

+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.73 0.679 18.41

 # Two-component error by variable is possible with both estimation methods
 # Variance by variable is supported by 'saem' and 'focei'
 f_nlmixr_fomc_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "saem",
   error_model = "obs_tc")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.782 0.02 0.803
f_nlmixr_fomc_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei",
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.775 0.024 0.799
f_nlmixr_fomc_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei",
   error_model = "obs_tc")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
@@ -4889,9 +795,9 @@ obtained by fitting the same model to a list of datasets using beta=exp(rx_expr_8);
 #> f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.173 0.405 8.575
f_nlmixr_dfop_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "saem",
+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 8.173 0.386 8.556
f_nlmixr_dfop_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "saem",
   error_model = "obs_tc")
-
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.824 0.024 0.851
f_nlmixr_dfop_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei",
+
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#> Error in configsaem(model = model, data = dat, inits = inits, mcmc = .mcmc,     ODEopt = .ODEopt, seed = .seed, distribution = .dist, DEBUG = .DEBUG,     addProp = .addProp, tol = .tol, itmax = .itmax, type = .type,     powRange = .powRange, lambdaRange = .lambdaRange): covariate(s) not found: f_parent_to_A1
#> Timing stopped at: 0.799 0.044 0.842
f_nlmixr_dfop_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei",
   error_model = "obs_tc")
 
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → creating full model...
#> → pruning branches (`if`/`else`)...
#> ✔ done
#> → loading into symengine environment...
#> ✔ done
#> → calculate jacobian
#> 
#> → calculate sensitivities
#> 
#> → calculate ∂(f)/∂(η)
#> 
#> → calculate ∂(R²)/∂(η)
#> 
#> → finding duplicate expressions in inner model...
#> 
#> → optimizing duplicate expressions in inner model...
#> 
#> → finding duplicate expressions in EBE model...
#> 
#> → optimizing duplicate expressions in EBE model...
#> 
#> → compiling inner model...
#>  
#> ✔ done
#> → finding duplicate expressions in FD model...
#> 
#> → optimizing duplicate expressions in FD model...
#> 
#> → compiling EBE model...
#>  
#> ✔ done
#> → compiling events FD model...
#>  
#> ✔ done
#> Model:
#> cmt(parent);
 #> cmt(A1);
@@ -4951,7 +857,7 @@ obtained by fitting the same model to a list of datasets using f_parent=1/(1+exp(-(ETA[3]+THETA[3])));
 #> g=1/(rx_expr_19);
 #> tad=tad();
-#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.44 0.876 18.31

+#> dosenum=dosenum();
#> Needed Covariates:
#> [1] "f_parent_to_A1" "CMT"           
#> Error in (function (data, inits, PKpars, model = NULL, pred = NULL, err = NULL,     lower = -Inf, upper = Inf, fixed = NULL, skipCov = NULL,     control = foceiControl(), thetaNames = NULL, etaNames = NULL,     etaMat = NULL, ..., env = NULL, keep = NULL, drop = NULL) {    set.seed(control$seed)    .pt <- proc.time()    RxODE::.setWarnIdSort(FALSE)    on.exit(RxODE::.setWarnIdSort(TRUE))    loadNamespace("n1qn1")    if (!RxODE::rxIs(control, "foceiControl")) {        control <- do.call(foceiControl, control)    }    if (is.null(env)) {        .ret <- new.env(parent = emptyenv())    }    else {        .ret <- env    }    .ret$origData <- data    .ret$etaNames <- etaNames    .ret$thetaFixed <- fixed    .ret$control <- control    .ret$control$focei.mu.ref <- integer(0)    if (is(model, "RxODE") || is(model, "character")) {        .ret$ODEmodel <- TRUE        if (class(pred) != "function") {            stop("pred must be a function specifying the prediction variables in this model.")        }    }    else {        .ret$ODEmodel <- TRUE        model <- RxODE::rxGetLin(PKpars)        pred <- eval(parse(text = "function(){return(Central);}"))    }    .square <- function(x) x * x    .ret$diagXformInv <- c(sqrt = ".square", log = "exp", identity = "identity")[control$diagXform]    if (is.null(err)) {        err <- eval(parse(text = paste0("function(){err", paste(inits$ERROR[[1]],             collapse = ""), "}")))    }    .covNames <- .parNames <- c()    .ret$adjLik <- control$adjLik    .mixed <- !is.null(inits$OMGA) && length(inits$OMGA) > 0    if (!exists("noLik", envir = .ret)) {        .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))        .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))        .ssAtol <- rep(control$ssAtol, length(RxODE::rxModelVars(model)$state))        .ssRtol <- rep(control$ssRtol, length(RxODE::rxModelVars(model)$state))        .ret$model <- RxODE::rxSymPySetupPred(model, pred, PKpars,             err, grad = (control$derivMethod == 2L), pred.minus.dv = TRUE,             sum.prod = control$sumProd, theta.derivs = FALSE,             optExpression = control$optExpression, interaction = (control$interaction ==                 1L), only.numeric = !.mixed, run.internal = TRUE,             addProp = control$addProp)        if (!is.null(.ret$model$inner)) {            .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.atol)))            .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.rtol)))            .ret$control$rxControl$atol <- .atol            .ret$control$rxControl$rtol <- .rtol            .ssAtol <- c(.ssAtol, rep(control$ssAtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssAtol)))            .ssRtol <- c(.ssRtol, rep(control$ssRtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                 length(.ssRtol)))            .ret$control$rxControl$ssAtol <- .ssAtol            .ret$control$rxControl$ssRtol <- .ssRtol        }        .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)        .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",             "ETA"), "[", numbers, "]", end), .covNames) == -1]        colnames(data) <- sapply(names(data), function(x) {            if (any(x == .covNames)) {                return(x)            }            else {                return(toupper(x))            }        })        .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),             RxODE::rxLhs(.ret$model$pred.only))        if (length(.lhs) > 0) {            .covNames <- .covNames[regexpr(rex::rex(start, or(.lhs),                 end), .covNames) == -1]        }        if (length(.covNames) > 0) {            if (!all(.covNames %in% names(data))) {                message("Model:")                RxODE::rxCat(.ret$model$pred.only)                message("Needed Covariates:")                nlmixrPrint(.covNames)                stop("Not all the covariates are in the dataset.")            }            message("Needed Covariates:")            print(.covNames)        }        .extraPars <- .ret$model$extra.pars    }    else {        if (.ret$noLik) {            .atol <- rep(control$atol, length(RxODE::rxModelVars(model)$state))            .rtol <- rep(control$rtol, length(RxODE::rxModelVars(model)$state))            .ret$model <- RxODE::rxSymPySetupPred(model, pred,                 PKpars, err, grad = FALSE, pred.minus.dv = TRUE,                 sum.prod = control$sumProd, theta.derivs = FALSE,                 optExpression = control$optExpression, run.internal = TRUE,                 only.numeric = TRUE, addProp = control$addProp)            if (!is.null(.ret$model$inner)) {                .atol <- c(.atol, rep(control$atolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.atol)))                .rtol <- c(.rtol, rep(control$rtolSens, length(RxODE::rxModelVars(.ret$model$inner)$state) -                   length(.rtol)))                .ret$control$rxControl$atol <- .atol                .ret$control$rxControl$rtol <- .rtol            }            .covNames <- .parNames <- RxODE::rxParams(.ret$model$pred.only)            .covNames <- .covNames[regexpr(rex::rex(start, or("THETA",                 "ETA"), "[", numbers, "]", end), .covNames) ==                 -1]            colnames(data) <- sapply(names(data), function(x) {                if (any(x == .covNames)) {                  return(x)                }                else {                  return(toupper(x))                }            })            .lhs <- c(names(RxODE::rxInits(.ret$model$pred.only)),                 RxODE::rxLhs(.ret$model$pred.only))            if (length(.lhs) > 0) {                .covNames <- .covNames[regexpr(rex::rex(start,                   or(.lhs), end), .covNames) == -1]            }            if (length(.covNames) > 0) {                if (!all(.covNames %in% names(data))) {                  message("Model:")                  RxODE::rxCat(.ret$model$pred.only)                  message("Needed Covariates:")                  nlmixrPrint(.covNames)                  stop("Not all the covariates are in the dataset.")                }                message("Needed Covariates:")                print(.covNames)            }            .extraPars <- .ret$model$extra.pars        }        else {            .extraPars <- NULL        }    }    .ret$skipCov <- skipCov    if (is.null(skipCov)) {        if (is.null(fixed)) {            .tmp <- rep(FALSE, length(inits$THTA))        }        else {            if (length(fixed) < length(inits$THTA)) {                .tmp <- c(fixed, rep(FALSE, length(inits$THTA) -                   length(fixed)))            }            else {                .tmp <- fixed[1:length(inits$THTA)]            }        }        if (exists("uif", envir = .ret)) {            .uifErr <- .ret$uif$ini$err[!is.na(.ret$uif$ini$ntheta)]            .uifErr <- sapply(.uifErr, function(x) {                if (is.na(x)) {                  return(FALSE)                }                return(!any(x == c("pow2", "tbs", "tbsYj")))            })            .tmp <- (.tmp | .uifErr)        }        .ret$skipCov <- c(.tmp, rep(TRUE, length(.extraPars)))        .ret$control$focei.mu.ref <- .ret$uif$focei.mu.ref    }    if (is.null(.extraPars)) {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)))    }    else {        .nms <- c(sprintf("THETA[%s]", seq_along(inits$THTA)),             sprintf("ERR[%s]", seq_along(.extraPars)))    }    if (!is.null(thetaNames) && (length(inits$THTA) + length(.extraPars)) ==         length(thetaNames)) {        .nms <- thetaNames    }    .ret$thetaNames <- .nms    .thetaReset$thetaNames <- .nms    if (length(lower) == 1) {        lower <- rep(lower, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        print(inits$THTA)        print(lower)        stop("Lower must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (length(upper) == 1) {        upper <- rep(upper, length(inits$THTA))    }    else if (length(lower) != length(inits$THTA)) {        stop("Upper must be a single constant for all the THETA lower bounds, or match the dimension of THETA.")    }    if (!is.null(.extraPars)) {        .ret$model$extra.pars <- eval(call(control$diagXform,             .ret$model$extra.pars))        if (length(.ret$model$extra.pars) > 0) {            inits$THTA <- c(inits$THTA, .ret$model$extra.pars)            .lowerErr <- rep(control$atol[1] * 10, length(.ret$model$extra.pars))            .upperErr <- rep(Inf, length(.ret$model$extra.pars))            lower <- c(lower, .lowerErr)            upper <- c(upper, .upperErr)        }    }    if (is.null(data$ID))         stop("\"ID\" not found in data")    if (is.null(data$DV))         stop("\"DV\" not found in data")    if (is.null(data$EVID))         data$EVID <- 0    if (is.null(data$AMT))         data$AMT <- 0    for (.v in c("TIME", "AMT", "DV", .covNames)) {        data[[.v]] <- as.double(data[[.v]])    }    .ret$dataSav <- data    .ds <- data[data$EVID != 0 & data$EVID != 2, c("ID", "TIME",         "AMT", "EVID", .covNames)]    .w <- which(tolower(names(data)) == "limit")    .limitName <- NULL    if (length(.w) == 1L) {        .limitName <- names(data)[.w]    }    .censName <- NULL    .w <- which(tolower(names(data)) == "cens")    if (length(.w) == 1L) {        .censName <- names(data[.w])    }    data <- data[data$EVID == 0 | data$EVID == 2, c("ID", "TIME",         "DV", "EVID", .covNames, .limitName, .censName)]    .w <- which(!(names(.ret$dataSav) %in% c(.covNames, keep)))    names(.ret$dataSav)[.w] <- tolower(names(.ret$dataSav[.w]))    if (.mixed) {        .lh <- .parseOM(inits$OMGA)        .nlh <- sapply(.lh, length)        .osplt <- rep(1:length(.lh), .nlh)        .lini <- list(inits$THTA, unlist(.lh))        .nlini <- sapply(.lini, length)        .nsplt <- rep(1:length(.lini), .nlini)        .om0 <- .genOM(.lh)        if (length(etaNames) == dim(.om0)[1]) {            .ret$etaNames <- .ret$etaNames        }        else {            .ret$etaNames <- sprintf("ETA[%d]", seq(1, dim(.om0)[1]))        }        .ret$rxInv <- RxODE::rxSymInvCholCreate(mat = .om0, diag.xform = control$diagXform)        .ret$xType <- .ret$rxInv$xType        .om0a <- .om0        .om0a <- .om0a/control$diagOmegaBoundLower        .om0b <- .om0        .om0b <- .om0b * control$diagOmegaBoundUpper        .om0a <- RxODE::rxSymInvCholCreate(mat = .om0a, diag.xform = control$diagXform)        .om0b <- RxODE::rxSymInvCholCreate(mat = .om0b, diag.xform = control$diagXform)        .omdf <- data.frame(a = .om0a$theta, m = .ret$rxInv$theta,             b = .om0b$theta, diag = .om0a$theta.diag)        .omdf$lower <- with(.omdf, ifelse(a > b, b, a))        .omdf$lower <- with(.omdf, ifelse(lower == m, -Inf, lower))        .omdf$lower <- with(.omdf, ifelse(!diag, -Inf, lower))        .omdf$upper <- with(.omdf, ifelse(a < b, b, a))        .omdf$upper <- with(.omdf, ifelse(upper == m, Inf, upper))        .omdf$upper <- with(.omdf, ifelse(!diag, Inf, upper))        .ret$control$nomega <- length(.omdf$lower)        .ret$control$neta <- sum(.omdf$diag)        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)        lower <- c(lower, .omdf$lower)        upper <- c(upper, .omdf$upper)    }    else {        .ret$control$nomega <- 0        .ret$control$neta <- 0        .ret$xType <- -1        .ret$control$ntheta <- length(lower)        .ret$control$nfixed <- sum(fixed)    }    .ret$lower <- lower    .ret$upper <- upper    .ret$thetaIni <- inits$THTA    .scaleC <- double(length(lower))    if (is.null(control$scaleC)) {        .scaleC <- rep(NA_real_, length(lower))    }    else {        .scaleC <- as.double(control$scaleC)        if (length(lower) > length(.scaleC)) {            .scaleC <- c(.scaleC, rep(NA_real_, length(lower) -                 length(.scaleC)))        }        else if (length(lower) < length(.scaleC)) {            .scaleC <- .scaleC[seq(1, length(lower))]            warning("scaleC control option has more options than estimated population parameters, please check.")        }    }    .ret$scaleC <- .scaleC    if (exists("uif", envir = .ret)) {        .ini <- as.data.frame(.ret$uif$ini)[!is.na(.ret$uif$ini$err),             c("est", "err", "ntheta")]        for (.i in seq_along(.ini$err)) {            if (is.na(.ret$scaleC[.ini$ntheta[.i]])) {                if (any(.ini$err[.i] == c("boxCox", "yeoJohnson",                   "pow2", "tbs", "tbsYj"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 1                }                else if (any(.ini$err[.i] == c("prop", "add",                   "norm", "dnorm", "logn", "dlogn", "lnorm",                   "dlnorm"))) {                  .ret$scaleC[.ini$ntheta[.i]] <- 0.5 * abs(.ini$est[.i])                }            }        }        for (.i in .ini$model$extraProps$powTheta) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- 1        }        .ini <- as.data.frame(.ret$uif$ini)        for (.i in .ini$model$extraProps$factorial) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i] +                   1))        }        for (.i in .ini$model$extraProps$gamma) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- abs(1/digamma(.ini$est[.i]))        }        for (.i in .ini$model$extraProps$log) {            if (is.na(.ret$scaleC[.i]))                 .ret$scaleC[.i] <- log(abs(.ini$est[.i])) * abs(.ini$est[.i])        }        for (.i in .ret$logitThetas) {            .b <- .ret$logitThetasLow[.i]            .c <- .ret$logitThetasHi[.i]            .a <- .ini$est[.i]            if (is.na(.ret$scaleC[.i])) {                .ret$scaleC[.i] <- 1 * (-.b + .c) * exp(-.a)/((1 +                   exp(-.a))^2 * (.b + 1 * (-.b + .c)/(1 + exp(-.a))))            }        }    }    names(.ret$thetaIni) <- sprintf("THETA[%d]", seq_along(.ret$thetaIni))    if (is.null(etaMat) & !is.null(control$etaMat)) {        .ret$etaMat <- control$etaMat    }    else {        .ret$etaMat <- etaMat    }    .ret$setupTime <- (proc.time() - .pt)["elapsed"]    if (exists("uif", envir = .ret)) {        .tmp <- .ret$uif$logThetasList        .ret$logThetas <- .tmp[[1]]        .ret$logThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasList        .ret$logitThetas <- .tmp[[1]]        .ret$logitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListLow        .ret$logitThetasLow <- .tmp[[1]]        .ret$logitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$logitThetasListHi        .ret$logitThetasHi <- .tmp[[1]]        .ret$logitThetasHiF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasList        .ret$probitThetas <- .tmp[[1]]        .ret$probitThetasF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListLow        .ret$probitThetasLow <- .tmp[[1]]        .ret$probitThetasLowF <- .tmp[[2]]        .tmp <- .ret$uif$probitThetasListHi        .ret$probitThetasHi <- .tmp[[1]]        .ret$probitThetasHiF <- .tmp[[2]]    }    else {        .ret$logThetasF <- integer(0)        .ret$logitThetasF <- integer(0)        .ret$logitThetasHiF <- numeric(0)        .ret$logitThetasLowF <- numeric(0)        .ret$logitThetas <- integer(0)        .ret$logitThetasHi <- numeric(0)        .ret$logitThetasLow <- numeric(0)        .ret$probitThetasF <- integer(0)        .ret$probitThetasHiF <- numeric(0)        .ret$probitThetasLowF <- numeric(0)        .ret$probitThetas <- integer(0)        .ret$probitThetasHi <- numeric(0)        .ret$probitThetasLow <- numeric(0)    }    if (exists("noLik", envir = .ret)) {        if (!.ret$noLik) {            .ret$.params <- c(sprintf("THETA[%d]", seq_along(.ret$thetaIni)),                 sprintf("ETA[%d]", seq(1, dim(.om0)[1])))            .ret$.thetan <- length(.ret$thetaIni)            .ret$nobs <- sum(data$EVID == 0)        }    }    .ret$control$printTop <- TRUE    .ret$control$nF <- 0    .est0 <- .ret$thetaIni    if (!is.null(.ret$model$pred.nolhs)) {        .ret$control$predNeq <- length(.ret$model$pred.nolhs$state)    }    else {        .ret$control$predNeq <- 0L    }    .fitFun <- function(.ret) {        this.env <- environment()        assign("err", "theta reset", this.env)        while (this.env$err == "theta reset") {            assign("err", "", this.env)            .ret0 <- tryCatch({                foceiFitCpp_(.ret)            }, error = function(e) {                if (regexpr("theta reset", e$message) != -1) {                  assign("zeroOuter", FALSE, this.env)                  assign("zeroGrad", FALSE, this.env)                  if (regexpr("theta reset0", e$message) != -1) {                    assign("zeroGrad", TRUE, this.env)                  }                  else if (regexpr("theta resetZ", e$message) !=                     -1) {                    assign("zeroOuter", TRUE, this.env)                  }                  assign("err", "theta reset", this.env)                }                else {                  assign("err", e$message, this.env)                }            })            if (this.env$err == "theta reset") {                .nm <- names(.ret$thetaIni)                .ret$thetaIni <- setNames(.thetaReset$thetaIni +                   0, .nm)                .ret$rxInv$theta <- .thetaReset$omegaTheta                .ret$control$printTop <- FALSE                .ret$etaMat <- .thetaReset$etaMat                .ret$control$etaMat <- .thetaReset$etaMat                .ret$control$maxInnerIterations <- .thetaReset$maxInnerIterations                .ret$control$nF <- .thetaReset$nF                .ret$control$gillRetC <- .thetaReset$gillRetC                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillRet <- .thetaReset$gillRet                .ret$control$gillDf <- .thetaReset$gillDf                .ret$control$gillDf2 <- .thetaReset$gillDf2                .ret$control$gillErr <- .thetaReset$gillErr                .ret$control$rEps <- .thetaReset$rEps                .ret$control$aEps <- .thetaReset$aEps                .ret$control$rEpsC <- .thetaReset$rEpsC                .ret$control$aEpsC <- .thetaReset$aEpsC                .ret$control$c1 <- .thetaReset$c1                .ret$control$c2 <- .thetaReset$c2                if (this.env$zeroOuter) {                  message("Posthoc reset")                  .ret$control$maxOuterIterations <- 0L                }                else if (this.env$zeroGrad) {                  message("Theta reset (zero gradient values); Switch to bobyqa")                  RxODE::rxReq("minqa")                  .ret$control$outerOptFun <- .bobyqa                  .ret$control$outerOpt <- -1L                }                else {                  message("Theta reset (ETA drift)")                }            }        }        if (this.env$err != "") {            stop(this.env$err)        }        else {            return(.ret0)        }    }    .ret0 <- try(.fitFun(.ret))    .n <- 1    while (inherits(.ret0, "try-error") && control$maxOuterIterations !=         0 && .n <= control$nRetries) {        message(sprintf("Restart %s", .n))        .ret$control$nF <- 0        .estNew <- .est0 + 0.2 * .n * abs(.est0) * stats::runif(length(.est0)) -             0.1 * .n        .estNew <- sapply(seq_along(.est0), function(.i) {            if (.ret$thetaFixed[.i]) {                return(.est0[.i])            }            else if (.estNew[.i] < lower[.i]) {                return(lower + (.Machine$double.eps)^(1/7))            }            else if (.estNew[.i] > upper[.i]) {                return(upper - (.Machine$double.eps)^(1/7))            }            else {                return(.estNew[.i])            }        })        .ret$thetaIni <- .estNew        .ret0 <- try(.fitFun(.ret))        .n <- .n + 1    }    if (inherits(.ret0, "try-error"))         stop("Could not fit data.")    .ret <- .ret0    if (exists("parHistData", .ret)) {        .tmp <- .ret$parHistData        .tmp <- .tmp[.tmp$type == "Unscaled", names(.tmp) !=             "type"]        .iter <- .tmp$iter        .tmp <- .tmp[, names(.tmp) != "iter"]        .ret$parHistStacked <- data.frame(stack(.tmp), iter = .iter)        names(.ret$parHistStacked) <- c("val", "par", "iter")        .ret$parHist <- data.frame(iter = .iter, .tmp)    }    if (.mixed) {        .etas <- .ret$ranef        .thetas <- .ret$fixef        .pars <- .Call(`_nlmixr_nlmixrParameters`, .thetas, .etas)        .ret$shrink <- .Call(`_nlmixr_calcShrinkOnly`, .ret$omega,             .pars$eta.lst, length(.etas$ID))        .updateParFixed(.ret)    }    else {        .updateParFixed(.ret)    }    if (!exists("table", .ret)) {        .ret$table <- tableControl()    }    if (control$calcTables) {        .ret <- addTable(.ret, updateObject = "no", keep = keep,             drop = drop, table = .ret$table)    }    .ret})(data = dat, inits = .FoceiInits, PKpars = .pars, model = .mod,     pred = function() {        return(nlmixr_pred)    }, err = uif$error, lower = uif$focei.lower, upper = uif$focei.upper,     fixed = uif$focei.fixed, thetaNames = uif$focei.names, etaNames = uif$eta.names,     control = control, env = env, keep = .keep, drop = .drop): Not all the covariates are in the dataset.
#> Timing stopped at: 17.5 0.646 18.15

 AIC(
   f_nlmixr_sfo_sfo_focei_const$nm,
   f_nlmixr_fomc_sfo_focei_const$nm,
diff --git a/man/nlmixr.mmkin.Rd b/man/nlmixr.mmkin.Rd
index 173b0d39..698c04f0 100644
--- a/man/nlmixr.mmkin.Rd
+++ b/man/nlmixr.mmkin.Rd
@@ -94,7 +94,8 @@ An dataframe suitable for use with \link[nlmixr:nlmixr]{nlmixr::nlmixr}
 \description{
 This function uses \code{\link[nlmixr:nlmixr]{nlmixr::nlmixr()}} as a backend for fitting nonlinear mixed
 effects models created from \link{mmkin} row objects using the Stochastic Approximation
-Expectation Maximisation algorithm (SAEM).
+Expectation Maximisation algorithm (SAEM) or First Order Conditional
+Estimation with Interaction (FOCEI).
 }
 \details{
 An mmkin row object is essentially a list of mkinfit objects that have been
@@ -110,20 +111,31 @@ f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP", "HS"), ds, quiet = TRUE, cores
 f_mmkin_parent_tc <- mmkin(c("SFO", "FOMC", "DFOP"), ds, error_model = "tc",
   cores = 1, quiet = TRUE)
 
-f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem")
-f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei")
+library(nlmixr)
+f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem",
+  control = saemControl(print = 0))
+f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei",
+  control = foceiControl(print = 0))
 
-f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem")
-f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei")
+f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem",
+  control = saemControl(print = 0))
+f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei",
+  control = foceiControl(print = 0))
 
-f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem")
-f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei")
+f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem",
+  control = saemControl(print = 0))
+f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei",
+  control = foceiControl(print = 0))
 
-f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem")
-f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei")
+f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem",
+  control = saemControl(print = 0))
+f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei",
+  control = foceiControl(print = 0))
 
-f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem")
-f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei")
+f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem",
+  control = saemControl(print = 0))
+f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei",
+  control = foceiControl(print = 0))
 
 AIC(
   f_nlmixr_sfo_saem$nm, f_nlmixr_sfo_focei$nm,
@@ -135,9 +147,8 @@ AIC(
 AIC(nlme(f_mmkin_parent["FOMC", ]))
 AIC(nlme(f_mmkin_parent["HS", ]))
 
-# nlme is comparable to nlmixr with focei, saem finds a better
-# solution, the two-component error model does not improve it
-plot(f_nlmixr_fomc_saem)
+# The FOCEI fit of FOMC with constant variance or the tc error model is best
+plot(f_nlmixr_fomc_saem_tc)
 
 sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
   A1 = mkinsub("SFO"))
-- 
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