From c6086d1dd97ad2d6420625de7b8009b1b0f85d06 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 18 Nov 2016 15:01:53 +0100 Subject: Static documentation rebuilt by pkgdown::build_site(run_dont_run = TRUE) Using branch 'jranke' on jranke/pkgdown, fixing issues hadley/pgkdown#178 and hadley/pkgdown#213 Remove plot=TRUE from mkinfit calls also in dontrun sections of examples to avoid a flood png files documenting the progress of the fit. --- docs/reference/mkinfit.html | 2169 +++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 2110 insertions(+), 59 deletions(-) (limited to 'docs/reference/mkinfit.html') diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index 891bc18b..f6ffd21d 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -359,15 +359,15 @@ fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE) summary(fit)
#> mkin version: 0.9.44.9000 #> R version: 3.3.2 -#> Date of fit: Thu Nov 17 22:56:57 2016 -#> Date of summary: Thu Nov 17 22:56:57 2016 +#> Date of fit: Fri Nov 18 15:19:37 2016 +#> Date of summary: Fri Nov 18 15:19:37 2016 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent #> #> Model predictions using solution type analytical #> -#> Fitted with method Port using 64 model solutions performed in 0.158 s +#> Fitted with method Port using 64 model solutions performed in 0.152 s #> #> Weighting: none #> @@ -436,7 +436,7 @@ m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet = TRUE)))
#> user system elapsed -#> 1.168 1.260 0.924
coef(fit)
#> parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink +#> 1.220 1.184 0.904
coef(fit)
#> parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink #> 99.59848 -3.03822 -2.98030 -5.24750
endpoints(fit)
#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 @@ -448,63 +448,2114 @@ #> DT50 DT90 #> parent 7.022929 23.32967 #> m1 131.760712 437.69961 -#>
## Not run: ------------------------------------ -# # deSolve is slower when no C compiler (gcc) was available during model generation -# print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D, -# solution_type = "deSolve"))) -# coef(fit.deSolve) -# endpoints(fit.deSolve) -## --------------------------------------------- +#>
+# deSolve is slower when no C compiler (gcc) was available during model generation +print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D, + solution_type = "deSolve")))
#> Model cost at call 1 : 18915.53 +#> Model cost at call 2 : 18915.53 +#> Model cost at call 6 : 11424.02 +#> Model cost at call 10 : 11424 +#> Model cost at call 12 : 4094.396 +#> Model cost at call 16 : 4094.396 +#> Model cost at call 19 : 1340.595 +#> Model cost at call 20 : 1340.593 +#> Model cost at call 25 : 1072.239 +#> Model cost at call 28 : 1072.236 +#> Model cost at call 30 : 874.2614 +#> Model cost at call 33 : 874.2611 +#> Model cost at call 35 : 616.2379 +#> Model cost at call 37 : 616.2374 +#> Model cost at call 40 : 467.4388 +#> Model cost at call 42 : 467.4382 +#> Model cost at call 46 : 398.2914 +#> Model cost at call 48 : 398.2914 +#> Model cost at call 49 : 398.2913 +#> Model cost at call 51 : 395.0712 +#> Model cost at call 54 : 395.0711 +#> Model cost at call 56 : 378.3298 +#> Model cost at call 59 : 378.3298 +#> Model cost at call 62 : 376.9812 +#> Model cost at call 64 : 376.9811 +#> Model cost at call 67 : 375.2085 +#> Model cost at call 69 : 375.2085 +#> Model cost at call 70 : 375.2085 +#> Model cost at call 71 : 375.2085 +#> Model cost at call 72 : 374.5723 +#> Model cost at call 74 : 374.5723 +#> Model cost at call 77 : 374.0075 +#> Model cost at call 79 : 374.0075 +#> Model cost at call 80 : 374.0075 +#> Model cost at call 82 : 373.1711 +#> Model cost at call 84 : 373.1711 +#> Model cost at call 87 : 372.6445 +#> Model cost at call 88 : 372.1614 +#> Model cost at call 90 : 372.1614 +#> Model cost at call 91 : 372.1614 +#> Model cost at call 94 : 371.6464 +#> Model cost at call 99 : 371.4299 +#> Model cost at call 101 : 371.4299 +#> Model cost at call 104 : 371.407 +#> Model cost at call 106 : 371.407 +#> Model cost at call 107 : 371.407 +#> Model cost at call 109 : 371.2524 +#> Model cost at call 113 : 371.2524 +#> Model cost at call 114 : 371.2136 +#> Model cost at call 115 : 371.2136 +#> Model cost at call 116 : 371.2136 +#> Model cost at call 119 : 371.2134 +#> Model cost at call 120 : 371.2134 +#> Model cost at call 122 : 371.2134 +#> Model cost at call 123 : 371.2134 +#> Model cost at call 125 : 371.2134 +#> Model cost at call 126 : 371.2134 +#> Model cost at call 135 : 371.2134 +#> Model cost at call 147 : 371.2134 +#> Model cost at call 152 : 371.2134 +#> Optimisation by method Port successfully terminated. +#> user system elapsed +#> 0.712 0.040 0.707
coef(fit.deSolve)
#> parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink +#> 99.59848 -3.03822 -2.98030 -5.24750
endpoints(fit.deSolve)
#> $ff +#> parent_sink parent_m1 m1_sink +#> 0.485524 0.514476 1.000000 +#> +#> $SFORB +#> logical(0) +#> +#> $distimes +#> DT50 DT90 +#> parent 7.022929 23.32967 +#> m1 131.760713 437.69961 +#>
# Use stepwise fitting, using optimised parameters from parent only fit, FOMC -## Not run: ------------------------------------ -# FOMC_SFO <- mkinmod( -# parent = mkinsub("FOMC", "m1"), -# m1 = mkinsub("SFO")) -# # Fit the model to the FOCUS example dataset D using defaults -# fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D) -# # Use starting parameters from parent only FOMC fit -# fit.FOMC = mkinfit("FOMC", FOCUS_2006_D, plot=TRUE) -# fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, -# parms.ini = fit.FOMC$bparms.ode, plot=TRUE) -# -# # Use stepwise fitting, using optimised parameters from parent only fit, SFORB -# SFORB_SFO <- mkinmod( -# parent = list(type = "SFORB", to = "m1", sink = TRUE), -# m1 = list(type = "SFO")) -# # Fit the model to the FOCUS example dataset D using defaults -# fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D) -# fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve") -# # Use starting parameters from parent only SFORB fit (not really needed in this case) -# fit.SFORB = mkinfit("SFORB", FOCUS_2006_D) -# fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode) -## --------------------------------------------- - -## Not run: ------------------------------------ -# # Weighted fits, including IRLS -# SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), -# m1 = mkinsub("SFO"), use_of_ff = "max") -# f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D) -# summary(f.noweight) -# f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs") -# summary(f.irls) -# f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean") -# summary(f.w.mean) -# f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value") -# summary(f.w.value) -## --------------------------------------------- - -## Not run: ------------------------------------ -# # Manual weighting -# dw <- FOCUS_2006_D -# errors <- c(parent = 2, m1 = 1) -# dw$err.man <- errors[FOCUS_2006_D$name] -# f.w.man <- mkinfit(SFO_SFO.ff, dw, err = "err.man") -# summary(f.w.man) -# f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", -# reweight.method = "obs") -# summary(f.w.man.irls) -## ---------------------------------------------
+ +FOMC_SFO <- mkinmod( + parent = mkinsub("FOMC", "m1"), + m1 = mkinsub("SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults +fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D)
#> Model cost at call 1 : 18857.28 +#> Model cost at call 4 : 18857.28 +#> Model cost at call 5 : 18857.28 +#> Model cost at call 8 : 15273.94 +#> Model cost at call 9 : 15273.93 +#> Model cost at call 12 : 15273.67 +#> Model cost at call 13 : 15273.64 +#> Model cost at call 14 : 12764.42 +#> Model cost at call 15 : 8382.7 +#> Model cost at call 20 : 8382.696 +#> Model cost at call 23 : 2729.177 +#> Model cost at call 24 : 2729.175 +#> Model cost at call 26 : 2729.164 +#> Model cost at call 30 : 2299.383 +#> Model cost at call 34 : 2299.379 +#> Model cost at call 35 : 2299.373 +#> Model cost at call 36 : 1944.782 +#> Model cost at call 40 : 1944.782 +#> Model cost at call 42 : 1328.087 +#> Model cost at call 43 : 908.661 +#> Model cost at call 44 : 908.6604 +#> Model cost at call 50 : 877.3556 +#> Model cost at call 51 : 877.3554 +#> Model cost at call 54 : 877.3546 +#> Model cost at call 56 : 769.5186 +#> Model cost at call 59 : 769.5157 +#> Model cost at call 62 : 690.3426 +#> Model cost at call 66 : 690.3425 +#> Model cost at call 68 : 608.4032 +#> Model cost at call 72 : 608.4031 +#> Model cost at call 73 : 608.4031 +#> Model cost at call 74 : 601.5178 +#> Model cost at call 78 : 601.5174 +#> Model cost at call 79 : 601.5174 +#> Model cost at call 80 : 459.9885 +#> Model cost at call 81 : 459.9883 +#> Model cost at call 83 : 459.9878 +#> Model cost at call 87 : 447.0145 +#> Model cost at call 91 : 447.0145 +#> Model cost at call 94 : 445.7322 +#> Model cost at call 97 : 445.7322 +#> Model cost at call 99 : 445.7322 +#> Model cost at call 100 : 444.6965 +#> Model cost at call 103 : 444.6965 +#> Model cost at call 106 : 442.9742 +#> Model cost at call 109 : 442.9742 +#> Model cost at call 112 : 439.9665 +#> Model cost at call 115 : 439.9665 +#> Model cost at call 116 : 439.9664 +#> Model cost at call 118 : 435.0752 +#> Model cost at call 121 : 435.0751 +#> Model cost at call 124 : 430.4718 +#> Model cost at call 127 : 430.4717 +#> Model cost at call 132 : 424.7004 +#> Model cost at call 134 : 424.7003 +#> Model cost at call 138 : 423.6102 +#> Model cost at call 141 : 423.6102 +#> Model cost at call 142 : 423.6102 +#> Model cost at call 144 : 421.1786 +#> Model cost at call 147 : 421.1786 +#> Model cost at call 148 : 421.1786 +#> Model cost at call 150 : 418.1431 +#> Model cost at call 151 : 412.8665 +#> Model cost at call 152 : 396.6067 +#> Model cost at call 154 : 396.6067 +#> Model cost at call 158 : 391.0492 +#> Model cost at call 160 : 391.0492 +#> Model cost at call 164 : 385.8205 +#> Model cost at call 165 : 385.8205 +#> Model cost at call 170 : 379.7674 +#> Model cost at call 171 : 379.7674 +#> Model cost at call 172 : 379.7674 +#> Model cost at call 176 : 374.9389 +#> Model cost at call 177 : 374.9389 +#> Model cost at call 182 : 372.727 +#> Model cost at call 185 : 372.727 +#> Model cost at call 188 : 371.5297 +#> Model cost at call 194 : 370.3738 +#> Model cost at call 195 : 370.3738 +#> Model cost at call 200 : 370.0182 +#> Model cost at call 206 : 369.8634 +#> Model cost at call 212 : 369.8188 +#> Model cost at call 213 : 369.8188 +#> Model cost at call 219 : 369.8114 +#> Model cost at call 221 : 369.8114 +#> Model cost at call 224 : 369.8114 +#> Model cost at call 226 : 369.8114 +#> Model cost at call 230 : 369.8105 +#> Model cost at call 231 : 369.8105 +#> Model cost at call 235 : 369.8105 +#> Model cost at call 236 : 369.8105 +#> Model cost at call 237 : 369.8105 +#> Model cost at call 238 : 369.8105 +#> Model cost at call 249 : 369.8105 +#> Model cost at call 260 : 369.8105 +#> Model cost at call 275 : 369.8105 +#> Model cost at call 276 : 369.8105 +#> Optimisation by method Port successfully terminated.
# Use starting parameters from parent only FOMC fit +fit.FOMC = mkinfit("FOMC", FOCUS_2006_D)
#> Model cost at call 1 : 3237.008 +#> Model cost at call 3 : 3237.007 +#> Model cost at call 6 : 671.2571 +#> Model cost at call 7 : 671.2559 +#> Model cost at call 8 : 671.2301 +#> Model cost at call 9 : 671.2249 +#> Model cost at call 10 : 468.4899 +#> Model cost at call 12 : 468.4899 +#> Model cost at call 14 : 371.3486 +#> Model cost at call 16 : 371.3485 +#> Model cost at call 18 : 346.2972 +#> Model cost at call 19 : 346.2971 +#> Model cost at call 20 : 346.297 +#> Model cost at call 21 : 346.2969 +#> Model cost at call 22 : 269.7053 +#> Model cost at call 23 : 269.7053 +#> Model cost at call 26 : 243.9936 +#> Model cost at call 27 : 235.1625 +#> Model cost at call 28 : 235.1624 +#> Model cost at call 30 : 235.1624 +#> Model cost at call 31 : 224.2195 +#> Model cost at call 35 : 218.1922 +#> Model cost at call 36 : 218.1922 +#> Model cost at call 38 : 218.1922 +#> Model cost at call 39 : 211.5012 +#> Model cost at call 41 : 211.5012 +#> Model cost at call 43 : 207.9511 +#> Model cost at call 44 : 207.9511 +#> Model cost at call 47 : 206.5377 +#> Model cost at call 51 : 205.8736 +#> Model cost at call 55 : 205.5625 +#> Model cost at call 59 : 205.4704 +#> Model cost at call 63 : 205.4499 +#> Model cost at call 67 : 205.448 +#> Model cost at call 69 : 205.448 +#> Model cost at call 70 : 205.448 +#> Model cost at call 73 : 205.448 +#> Model cost at call 74 : 205.4478 +#> Model cost at call 75 : 205.4478 +#> Model cost at call 77 : 205.4478 +#> Model cost at call 79 : 205.4478 +#> Model cost at call 84 : 205.4478 +#> Model cost at call 95 : 205.4478 +#> Model cost at call 98 : 205.4478 +#> Optimisation by method Port successfully terminated.
fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, + parms.ini = fit.FOMC$bparms.ode)
#> Model cost at call 1 : 15169.96 +#> Model cost at call 2 : 15169.96 +#> Model cost at call 7 : 8247.462 +#> Model cost at call 14 : 6734.371 +#> Model cost at call 15 : 6734.339 +#> Model cost at call 16 : 6734.136 +#> Model cost at call 20 : 4855.056 +#> Model cost at call 24 : 4855.038 +#> Model cost at call 27 : 1239.986 +#> Model cost at call 29 : 1239.985 +#> Model cost at call 34 : 1030.523 +#> Model cost at call 38 : 1030.523 +#> Model cost at call 40 : 894.2766 +#> Model cost at call 43 : 894.275 +#> Model cost at call 46 : 750.3629 +#> Model cost at call 49 : 750.3623 +#> Model cost at call 52 : 627.6819 +#> Model cost at call 55 : 627.6818 +#> Model cost at call 58 : 546.2947 +#> Model cost at call 61 : 546.2944 +#> Model cost at call 65 : 502.5529 +#> Model cost at call 69 : 502.5525 +#> Model cost at call 70 : 502.5525 +#> Model cost at call 71 : 475.2423 +#> Model cost at call 72 : 465.5298 +#> Model cost at call 75 : 465.5298 +#> Model cost at call 76 : 465.5297 +#> Model cost at call 78 : 464.9476 +#> Model cost at call 81 : 464.9476 +#> Model cost at call 82 : 464.9473 +#> Model cost at call 84 : 426.9626 +#> Model cost at call 88 : 426.9626 +#> Model cost at call 90 : 414.5235 +#> Model cost at call 93 : 414.5234 +#> Model cost at call 96 : 412.1478 +#> Model cost at call 99 : 412.1477 +#> Model cost at call 100 : 412.1477 +#> Model cost at call 101 : 412.1477 +#> Model cost at call 102 : 394.146 +#> Model cost at call 105 : 394.146 +#> Model cost at call 106 : 394.146 +#> Model cost at call 107 : 394.146 +#> Model cost at call 108 : 384.2002 +#> Model cost at call 112 : 384.2001 +#> Model cost at call 113 : 384.2001 +#> Model cost at call 115 : 380.5495 +#> Model cost at call 119 : 380.5494 +#> Model cost at call 120 : 380.5494 +#> Model cost at call 121 : 378.4803 +#> Model cost at call 123 : 378.4802 +#> Model cost at call 124 : 378.4792 +#> Model cost at call 127 : 374.8432 +#> Model cost at call 129 : 374.8431 +#> Model cost at call 133 : 372.8364 +#> Model cost at call 136 : 372.8364 +#> Model cost at call 137 : 372.8363 +#> Model cost at call 138 : 372.8363 +#> Model cost at call 141 : 372.668 +#> Model cost at call 145 : 372.6679 +#> Model cost at call 147 : 372.5882 +#> Model cost at call 150 : 372.5882 +#> Model cost at call 153 : 372.4828 +#> Model cost at call 156 : 372.4828 +#> Model cost at call 159 : 372.3639 +#> Model cost at call 162 : 372.3639 +#> Model cost at call 163 : 372.3639 +#> Model cost at call 164 : 372.3639 +#> Model cost at call 165 : 372.1959 +#> Model cost at call 168 : 372.1959 +#> Model cost at call 171 : 371.9627 +#> Model cost at call 172 : 371.7467 +#> Model cost at call 173 : 371.1161 +#> Model cost at call 174 : 370.3326 +#> Model cost at call 177 : 370.3326 +#> Model cost at call 178 : 370.3326 +#> Model cost at call 180 : 370.3267 +#> Model cost at call 186 : 370.0471 +#> Model cost at call 187 : 370.0471 +#> Model cost at call 193 : 369.9649 +#> Model cost at call 194 : 369.9649 +#> Model cost at call 196 : 369.9649 +#> Model cost at call 199 : 369.8684 +#> Model cost at call 200 : 369.8684 +#> Model cost at call 204 : 369.8684 +#> Model cost at call 206 : 369.8349 +#> Model cost at call 207 : 369.8349 +#> Model cost at call 209 : 369.8349 +#> Model cost at call 210 : 369.8349 +#> Model cost at call 211 : 369.8349 +#> Model cost at call 212 : 369.8105 +#> Model cost at call 214 : 369.8105 +#> Model cost at call 218 : 369.8105 +#> Model cost at call 220 : 369.8105 +#> Model cost at call 225 : 369.8105 +#> Model cost at call 229 : 369.8105 +#> Model cost at call 231 : 369.8105 +#> Model cost at call 232 : 369.8105 +#> Model cost at call 236 : 369.8105 +#> Model cost at call 239 : 369.8105 +#> Model cost at call 240 : 369.8105 +#> Model cost at call 255 : 369.8105 +#> Model cost at call 258 : 369.8105 +#> Optimisation by method Port successfully terminated.
+# Use stepwise fitting, using optimised parameters from parent only fit, SFORB +SFORB_SFO <- mkinmod( + parent = list(type = "SFORB", to = "m1", sink = TRUE), + m1 = list(type = "SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults +fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D)
#> Model cost at call 1 : 19233.21 +#> Model cost at call 2 : 19233.21 +#> Model cost at call 5 : 19233.21 +#> Model cost at call 8 : 14482.65 +#> Model cost at call 11 : 14482.51 +#> Model cost at call 13 : 14482.17 +#> Model cost at call 15 : 6973.814 +#> Model cost at call 16 : 5161.041 +#> Model cost at call 17 : 5161.029 +#> Model cost at call 22 : 5161.026 +#> Model cost at call 24 : 3249.595 +#> Model cost at call 26 : 3249.595 +#> Model cost at call 27 : 3249.519 +#> Model cost at call 31 : 2615.891 +#> Model cost at call 32 : 2615.888 +#> Model cost at call 39 : 989.1788 +#> Model cost at call 44 : 989.1772 +#> Model cost at call 45 : 989.1771 +#> Model cost at call 47 : 647.4307 +#> Model cost at call 50 : 647.4302 +#> Model cost at call 51 : 647.4261 +#> Model cost at call 54 : 626.7937 +#> Model cost at call 55 : 626.7935 +#> Model cost at call 56 : 626.7931 +#> Model cost at call 61 : 527.9042 +#> Model cost at call 62 : 527.9041 +#> Model cost at call 68 : 505.8828 +#> Model cost at call 70 : 505.8828 +#> Model cost at call 73 : 505.8827 +#> Model cost at call 75 : 452.8932 +#> Model cost at call 77 : 452.893 +#> Model cost at call 82 : 414.4918 +#> Model cost at call 83 : 414.4918 +#> Model cost at call 84 : 414.4918 +#> Model cost at call 88 : 414.4917 +#> Model cost at call 89 : 408.2617 +#> Model cost at call 90 : 408.2616 +#> Model cost at call 91 : 408.2616 +#> Model cost at call 95 : 408.2615 +#> Model cost at call 96 : 384.4461 +#> Model cost at call 102 : 384.4461 +#> Model cost at call 104 : 383.4905 +#> Model cost at call 105 : 383.4905 +#> Model cost at call 106 : 383.4905 +#> Model cost at call 109 : 383.4904 +#> Model cost at call 111 : 381.8828 +#> Model cost at call 112 : 381.8827 +#> Model cost at call 118 : 380.8499 +#> Model cost at call 120 : 380.8499 +#> Model cost at call 123 : 380.8499 +#> Model cost at call 125 : 379.1403 +#> Model cost at call 127 : 379.1402 +#> Model cost at call 132 : 376.4962 +#> Model cost at call 133 : 373.0958 +#> Model cost at call 134 : 365.247 +#> Model cost at call 137 : 365.2469 +#> Model cost at call 142 : 360.8231 +#> Model cost at call 143 : 360.8231 +#> Model cost at call 146 : 360.8231 +#> Model cost at call 148 : 360.8231 +#> Model cost at call 149 : 358.3976 +#> Model cost at call 152 : 358.3976 +#> Model cost at call 154 : 358.3976 +#> Model cost at call 156 : 355.9066 +#> Model cost at call 157 : 355.9066 +#> Model cost at call 163 : 354.3386 +#> Model cost at call 164 : 353.6335 +#> Model cost at call 172 : 353.2094 +#> Model cost at call 173 : 353.2094 +#> Model cost at call 174 : 353.2093 +#> Model cost at call 177 : 353.2093 +#> Model cost at call 178 : 353.2093 +#> Model cost at call 179 : 352.6641 +#> Model cost at call 182 : 352.6641 +#> Model cost at call 183 : 352.6641 +#> Model cost at call 186 : 352.4908 +#> Model cost at call 187 : 352.4429 +#> Model cost at call 195 : 352.3246 +#> Model cost at call 203 : 352.2858 +#> Model cost at call 204 : 352.2858 +#> Model cost at call 205 : 352.2858 +#> Model cost at call 206 : 352.2858 +#> Model cost at call 207 : 352.2858 +#> Model cost at call 210 : 352.2332 +#> Model cost at call 211 : 352.2081 +#> Model cost at call 214 : 352.2081 +#> Model cost at call 216 : 352.2081 +#> Model cost at call 218 : 352.2049 +#> Model cost at call 219 : 352.2049 +#> Model cost at call 220 : 352.2049 +#> Model cost at call 226 : 352.2048 +#> Model cost at call 228 : 352.2048 +#> Model cost at call 231 : 352.2048 +#> Model cost at call 232 : 352.2048 +#> Model cost at call 238 : 352.2048 +#> Model cost at call 239 : 352.2048 +#> Model cost at call 251 : 352.2048 +#> Model cost at call 264 : 352.2048 +#> Model cost at call 283 : 352.2048 +#> Model cost at call 284 : 352.2048 +#> Model cost at call 285 : 352.2048 +#> Model cost at call 286 : 352.2048 +#> Optimisation by method Port successfully terminated.
fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve")
#> Model cost at call 1 : 19233.21 +#> Model cost at call 2 : 19233.21 +#> Model cost at call 5 : 19233.21 +#> Model cost at call 8 : 14482.65 +#> Model cost at call 11 : 14482.51 +#> Model cost at call 13 : 14482.17 +#> Model cost at call 15 : 6973.814 +#> Model cost at call 16 : 5161.041 +#> Model cost at call 17 : 5161.029 +#> Model cost at call 22 : 5161.026 +#> Model cost at call 24 : 3249.595 +#> Model cost at call 26 : 3249.595 +#> Model cost at call 27 : 3249.519 +#> Model cost at call 31 : 2615.891 +#> Model cost at call 32 : 2615.888 +#> Model cost at call 39 : 989.1788 +#> Model cost at call 44 : 989.1772 +#> Model cost at call 45 : 989.1771 +#> Model cost at call 47 : 647.4307 +#> Model cost at call 50 : 647.4302 +#> Model cost at call 51 : 647.4261 +#> Model cost at call 54 : 626.7937 +#> Model cost at call 55 : 626.7935 +#> Model cost at call 56 : 626.7931 +#> Model cost at call 61 : 527.9042 +#> Model cost at call 62 : 527.9041 +#> Model cost at call 68 : 505.8828 +#> Model cost at call 70 : 505.8828 +#> Model cost at call 73 : 505.8827 +#> Model cost at call 75 : 452.8932 +#> Model cost at call 77 : 452.893 +#> Model cost at call 82 : 414.4918 +#> Model cost at call 83 : 414.4918 +#> Model cost at call 84 : 414.4918 +#> Model cost at call 88 : 414.4917 +#> Model cost at call 89 : 408.2617 +#> Model cost at call 90 : 408.2616 +#> Model cost at call 91 : 408.2616 +#> Model cost at call 95 : 408.2615 +#> Model cost at call 96 : 384.4461 +#> Model cost at call 102 : 384.4461 +#> Model cost at call 104 : 383.4905 +#> Model cost at call 105 : 383.4905 +#> Model cost at call 106 : 383.4905 +#> Model cost at call 109 : 383.4904 +#> Model cost at call 111 : 381.8828 +#> Model cost at call 112 : 381.8827 +#> Model cost at call 118 : 380.8499 +#> Model cost at call 120 : 380.8499 +#> Model cost at call 123 : 380.8499 +#> Model cost at call 125 : 379.1403 +#> Model cost at call 127 : 379.1402 +#> Model cost at call 132 : 376.4962 +#> Model cost at call 133 : 373.0958 +#> Model cost at call 134 : 365.247 +#> Model cost at call 137 : 365.2469 +#> Model cost at call 142 : 360.8231 +#> Model cost at call 143 : 360.8231 +#> Model cost at call 146 : 360.8231 +#> Model cost at call 148 : 360.8231 +#> Model cost at call 149 : 358.3976 +#> Model cost at call 152 : 358.3976 +#> Model cost at call 154 : 358.3976 +#> Model cost at call 156 : 355.9066 +#> Model cost at call 157 : 355.9066 +#> Model cost at call 163 : 354.3386 +#> Model cost at call 164 : 353.6335 +#> Model cost at call 172 : 353.2094 +#> Model cost at call 173 : 353.2094 +#> Model cost at call 174 : 353.2093 +#> Model cost at call 177 : 353.2093 +#> Model cost at call 178 : 353.2093 +#> Model cost at call 179 : 352.6641 +#> Model cost at call 182 : 352.6641 +#> Model cost at call 183 : 352.6641 +#> Model cost at call 186 : 352.4908 +#> Model cost at call 187 : 352.4429 +#> Model cost at call 195 : 352.3246 +#> Model cost at call 203 : 352.2858 +#> Model cost at call 204 : 352.2858 +#> Model cost at call 205 : 352.2858 +#> Model cost at call 206 : 352.2858 +#> Model cost at call 207 : 352.2858 +#> Model cost at call 210 : 352.2332 +#> Model cost at call 211 : 352.2081 +#> Model cost at call 214 : 352.2081 +#> Model cost at call 216 : 352.2081 +#> Model cost at call 218 : 352.2049 +#> Model cost at call 219 : 352.2049 +#> Model cost at call 220 : 352.2049 +#> Model cost at call 226 : 352.2048 +#> Model cost at call 228 : 352.2048 +#> Model cost at call 231 : 352.2048 +#> Model cost at call 232 : 352.2048 +#> Model cost at call 238 : 352.2048 +#> Model cost at call 239 : 352.2048 +#> Model cost at call 251 : 352.2048 +#> Model cost at call 264 : 352.2048 +#> Model cost at call 283 : 352.2048 +#> Model cost at call 284 : 352.2048 +#> Model cost at call 285 : 352.2048 +#> Model cost at call 286 : 352.2048 +#> Optimisation by method Port successfully terminated.
# Use starting parameters from parent only SFORB fit (not really needed in this case) +fit.SFORB = mkinfit("SFORB", FOCUS_2006_D)
#> Model cost at call 1 : 10426.65 +#> Model cost at call 3 : 10426.65 +#> Model cost at call 6 : 1995.326 +#> Model cost at call 7 : 1995.322 +#> Model cost at call 8 : 1995.14 +#> Model cost at call 11 : 718.5568 +#> Model cost at call 12 : 718.5566 +#> Model cost at call 13 : 718.5563 +#> Model cost at call 16 : 408.9208 +#> Model cost at call 17 : 408.9204 +#> Model cost at call 18 : 408.9204 +#> Model cost at call 20 : 408.9203 +#> Model cost at call 21 : 402.7935 +#> Model cost at call 22 : 402.793 +#> Model cost at call 26 : 202.0443 +#> Model cost at call 28 : 202.0443 +#> Model cost at call 30 : 202.0443 +#> Model cost at call 31 : 196.438 +#> Model cost at call 36 : 196.1947 +#> Model cost at call 37 : 196.1947 +#> Model cost at call 41 : 192.9338 +#> Model cost at call 43 : 192.9338 +#> Model cost at call 45 : 192.9338 +#> Model cost at call 46 : 191.6452 +#> Model cost at call 47 : 191.6452 +#> Model cost at call 51 : 188.9328 +#> Model cost at call 54 : 188.9328 +#> Model cost at call 55 : 188.9328 +#> Model cost at call 56 : 183.6499 +#> Model cost at call 59 : 183.6499 +#> Model cost at call 62 : 181.9039 +#> Model cost at call 67 : 179.0543 +#> Model cost at call 68 : 179.0543 +#> Model cost at call 69 : 179.0543 +#> Model cost at call 70 : 179.0543 +#> Model cost at call 72 : 176.749 +#> Model cost at call 73 : 176.2321 +#> Model cost at call 74 : 176.232 +#> Model cost at call 75 : 176.232 +#> Model cost at call 76 : 176.232 +#> Model cost at call 78 : 175.3914 +#> Model cost at call 79 : 175.3914 +#> Model cost at call 81 : 175.3913 +#> Model cost at call 83 : 174.6257 +#> Model cost at call 84 : 174.6257 +#> Model cost at call 89 : 174.1476 +#> Model cost at call 92 : 174.1476 +#> Model cost at call 93 : 174.1476 +#> Model cost at call 94 : 173.8512 +#> Model cost at call 99 : 173.6987 +#> Model cost at call 104 : 173.6813 +#> Model cost at call 105 : 173.6813 +#> Model cost at call 106 : 173.6813 +#> Model cost at call 107 : 173.6813 +#> Model cost at call 108 : 173.6813 +#> Model cost at call 109 : 173.6802 +#> Model cost at call 110 : 173.6802 +#> Model cost at call 111 : 173.6802 +#> Model cost at call 112 : 173.6802 +#> Model cost at call 113 : 173.6802 +#> Model cost at call 114 : 173.6799 +#> Model cost at call 116 : 173.6799 +#> Model cost at call 118 : 173.6799 +#> Model cost at call 119 : 173.6799 +#> Model cost at call 120 : 173.6799 +#> Model cost at call 129 : 173.6799 +#> Model cost at call 141 : 173.6799 +#> Optimisation by method Port successfully terminated.
fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode)
#> Model cost at call 1 : 18365.33 +#> Model cost at call 2 : 18365.33 +#> Model cost at call 8 : 11666.4 +#> Model cost at call 9 : 10992.15 +#> Model cost at call 10 : 10992.13 +#> Model cost at call 11 : 10991.95 +#> Model cost at call 12 : 10991.17 +#> Model cost at call 14 : 10990.65 +#> Model cost at call 17 : 3940.801 +#> Model cost at call 20 : 3940.8 +#> Model cost at call 22 : 3940.798 +#> Model cost at call 24 : 3241.199 +#> Model cost at call 27 : 3241.198 +#> Model cost at call 30 : 3241.192 +#> Model cost at call 31 : 1518.749 +#> Model cost at call 37 : 1518.747 +#> Model cost at call 39 : 1091.836 +#> Model cost at call 42 : 1091.835 +#> Model cost at call 43 : 1091.835 +#> Model cost at call 44 : 1091.804 +#> Model cost at call 46 : 927.8538 +#> Model cost at call 49 : 927.8529 +#> Model cost at call 53 : 638.102 +#> Model cost at call 56 : 638.1019 +#> Model cost at call 58 : 638.1018 +#> Model cost at call 61 : 560.4352 +#> Model cost at call 62 : 560.435 +#> Model cost at call 63 : 560.4327 +#> Model cost at call 68 : 423.9629 +#> Model cost at call 69 : 423.9629 +#> Model cost at call 70 : 423.9629 +#> Model cost at call 71 : 423.9628 +#> Model cost at call 73 : 423.9628 +#> Model cost at call 75 : 395.8015 +#> Model cost at call 78 : 395.8013 +#> Model cost at call 79 : 395.8013 +#> Model cost at call 83 : 365.6975 +#> Model cost at call 84 : 365.6975 +#> Model cost at call 88 : 365.6975 +#> Model cost at call 91 : 362.9843 +#> Model cost at call 93 : 362.9843 +#> Model cost at call 98 : 361.5506 +#> Model cost at call 99 : 361.5506 +#> Model cost at call 100 : 361.5505 +#> Model cost at call 105 : 359.0492 +#> Model cost at call 106 : 359.0492 +#> Model cost at call 112 : 357.6574 +#> Model cost at call 113 : 357.6574 +#> Model cost at call 114 : 357.6574 +#> Model cost at call 115 : 357.6574 +#> Model cost at call 119 : 355.4518 +#> Model cost at call 120 : 355.4518 +#> Model cost at call 127 : 354.9045 +#> Model cost at call 129 : 354.9045 +#> Model cost at call 131 : 354.9045 +#> Model cost at call 134 : 354.4168 +#> Model cost at call 135 : 354.4168 +#> Model cost at call 137 : 354.4167 +#> Model cost at call 141 : 353.7901 +#> Model cost at call 142 : 353.7901 +#> Model cost at call 143 : 353.7899 +#> Model cost at call 149 : 353.3233 +#> Model cost at call 151 : 353.3233 +#> Model cost at call 154 : 353.3233 +#> Model cost at call 156 : 353.2939 +#> Model cost at call 158 : 353.2938 +#> Model cost at call 159 : 353.2938 +#> Model cost at call 160 : 353.2938 +#> Model cost at call 163 : 353.0571 +#> Model cost at call 165 : 353.0571 +#> Model cost at call 170 : 352.9457 +#> Model cost at call 171 : 352.7458 +#> Model cost at call 173 : 352.7457 +#> Model cost at call 178 : 352.6377 +#> Model cost at call 180 : 352.6377 +#> Model cost at call 183 : 352.6377 +#> Model cost at call 185 : 352.5377 +#> Model cost at call 187 : 352.5377 +#> Model cost at call 188 : 352.5377 +#> Model cost at call 191 : 352.5377 +#> Model cost at call 193 : 352.4479 +#> Model cost at call 195 : 352.4479 +#> Model cost at call 198 : 352.4479 +#> Model cost at call 200 : 352.4021 +#> Model cost at call 202 : 352.4021 +#> Model cost at call 205 : 352.4021 +#> Model cost at call 207 : 352.3465 +#> Model cost at call 210 : 352.3465 +#> Model cost at call 214 : 352.3031 +#> Model cost at call 216 : 352.3031 +#> Model cost at call 221 : 352.2632 +#> Model cost at call 223 : 352.2632 +#> Model cost at call 228 : 352.2367 +#> Model cost at call 230 : 352.2367 +#> Model cost at call 231 : 352.2367 +#> Model cost at call 233 : 352.2367 +#> Model cost at call 235 : 352.215 +#> Model cost at call 238 : 352.215 +#> Model cost at call 239 : 352.215 +#> Model cost at call 242 : 352.207 +#> Model cost at call 245 : 352.207 +#> Model cost at call 250 : 352.2053 +#> Model cost at call 251 : 352.2053 +#> Model cost at call 253 : 352.2053 +#> Model cost at call 256 : 352.2053 +#> Model cost at call 258 : 352.2053 +#> Model cost at call 259 : 352.2052 +#> Model cost at call 260 : 352.2052 +#> Model cost at call 263 : 352.2052 +#> Model cost at call 271 : 352.2048 +#> Model cost at call 273 : 352.2048 +#> Model cost at call 274 : 352.2048 +#> Model cost at call 281 : 352.2048 +#> Model cost at call 282 : 352.2048 +#> Model cost at call 286 : 352.2048 +#> Model cost at call 289 : 352.2048 +#> Model cost at call 294 : 352.2048 +#> Model cost at call 296 : 352.2048 +#> Model cost at call 300 : 352.2048 +#> Model cost at call 307 : 352.2048 +#> Model cost at call 325 : 352.2048 +#> Model cost at call 331 : 352.2048 +#> Model cost at call 333 : 352.2048 +#> Optimisation by method Port successfully terminated.
+ + +# Weighted fits, including IRLS +SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), + m1 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D)
#> Model cost at call 1 : 15156.12 +#> Model cost at call 2 : 15156.12 +#> Model cost at call 6 : 8243.644 +#> Model cost at call 12 : 6290.714 +#> Model cost at call 13 : 6290.684 +#> Model cost at call 15 : 6290.453 +#> Model cost at call 18 : 1700.75 +#> Model cost at call 20 : 1700.612 +#> Model cost at call 24 : 1190.923 +#> Model cost at call 26 : 1190.922 +#> Model cost at call 29 : 1017.417 +#> Model cost at call 31 : 1017.417 +#> Model cost at call 33 : 1017.416 +#> Model cost at call 34 : 644.0471 +#> Model cost at call 36 : 644.0469 +#> Model cost at call 38 : 644.0468 +#> Model cost at call 39 : 590.5024 +#> Model cost at call 41 : 590.5021 +#> Model cost at call 43 : 590.5015 +#> Model cost at call 44 : 543.2187 +#> Model cost at call 45 : 543.2183 +#> Model cost at call 46 : 543.2182 +#> Model cost at call 50 : 391.348 +#> Model cost at call 51 : 391.3479 +#> Model cost at call 56 : 386.4789 +#> Model cost at call 58 : 386.4789 +#> Model cost at call 60 : 386.4779 +#> Model cost at call 61 : 384.0686 +#> Model cost at call 63 : 384.0686 +#> Model cost at call 66 : 382.7812 +#> Model cost at call 68 : 382.7812 +#> Model cost at call 70 : 382.7812 +#> Model cost at call 71 : 378.9272 +#> Model cost at call 73 : 378.9272 +#> Model cost at call 75 : 378.9272 +#> Model cost at call 76 : 377.4846 +#> Model cost at call 78 : 377.4846 +#> Model cost at call 81 : 375.9738 +#> Model cost at call 83 : 375.9738 +#> Model cost at call 86 : 375.3387 +#> Model cost at call 88 : 375.3387 +#> Model cost at call 91 : 374.5774 +#> Model cost at call 93 : 374.5774 +#> Model cost at call 95 : 374.5774 +#> Model cost at call 96 : 373.5447 +#> Model cost at call 100 : 373.5446 +#> Model cost at call 102 : 373.2643 +#> Model cost at call 104 : 373.2643 +#> Model cost at call 107 : 372.6799 +#> Model cost at call 111 : 372.6798 +#> Model cost at call 114 : 372.6325 +#> Model cost at call 116 : 372.6325 +#> Model cost at call 119 : 372.6159 +#> Model cost at call 121 : 372.6159 +#> Model cost at call 123 : 372.6159 +#> Model cost at call 124 : 372.5845 +#> Model cost at call 126 : 372.5845 +#> Model cost at call 129 : 372.5375 +#> Model cost at call 130 : 372.4771 +#> Model cost at call 131 : 372.2008 +#> Model cost at call 132 : 371.4923 +#> Model cost at call 134 : 371.4923 +#> Model cost at call 137 : 371.3022 +#> Model cost at call 139 : 371.3022 +#> Model cost at call 143 : 371.2271 +#> Model cost at call 144 : 371.2271 +#> Model cost at call 148 : 371.2202 +#> Model cost at call 149 : 371.215 +#> Model cost at call 152 : 371.215 +#> Model cost at call 154 : 371.2136 +#> Model cost at call 155 : 371.2136 +#> Model cost at call 156 : 371.2136 +#> Model cost at call 160 : 371.2134 +#> Model cost at call 164 : 371.2134 +#> Model cost at call 167 : 371.2134 +#> Optimisation by method Port successfully terminated.
summary(f.noweight)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:19:47 2016 +#> Date of summary: Fri Nov 18 15:19:47 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 185 model solutions performed in 0.748 s +#> +#> Weighting: none +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 99.60000 1.61400 96.3300 102.9000 +#> log_k_parent -2.31600 0.04187 -2.4010 -2.2310 +#> log_k_m1 -5.24800 0.13610 -5.5230 -4.9720 +#> f_parent_ilr_1 0.04096 0.06477 -0.0904 0.1723 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.0000 0.5178 -0.1701 -0.5489 +#> log_k_parent 0.5178 1.0000 -0.3285 -0.5451 +#> log_k_m1 -0.1701 -0.3285 1.0000 0.7466 +#> f_parent_ilr_1 -0.5489 -0.5451 0.7466 1.0000 +#> +#> Residual standard error: 3.211 on 36 degrees of freedom +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 99.600000 61.720 2.024e-38 96.330000 1.029e+02 +#> k_parent 0.098700 23.880 5.701e-24 0.090660 1.074e-01 +#> k_m1 0.005261 7.349 5.758e-09 0.003992 6.933e-03 +#> f_parent_to_m1 0.514500 22.490 4.374e-23 0.468100 5.606e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.398 4 15 +#> parent 6.459 2 7 +#> m1 4.690 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5145 +#> parent_sink 0.4855 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 7.023 23.33 +#> m1 131.761 437.70 +#> +#> Data: +#> time variable observed predicted residual +#> 0 parent 99.46 9.960e+01 -1.385e-01 +#> 0 parent 102.04 9.960e+01 2.442e+00 +#> 1 parent 93.50 9.024e+01 3.262e+00 +#> 1 parent 92.50 9.024e+01 2.262e+00 +#> 3 parent 63.23 7.407e+01 -1.084e+01 +#> 3 parent 68.99 7.407e+01 -5.083e+00 +#> 7 parent 52.32 4.991e+01 2.408e+00 +#> 7 parent 55.13 4.991e+01 5.218e+00 +#> 14 parent 27.27 2.501e+01 2.257e+00 +#> 14 parent 26.64 2.501e+01 1.627e+00 +#> 21 parent 11.50 1.253e+01 -1.035e+00 +#> 21 parent 11.64 1.253e+01 -8.946e-01 +#> 35 parent 2.85 3.148e+00 -2.979e-01 +#> 35 parent 2.91 3.148e+00 -2.379e-01 +#> 50 parent 0.69 7.162e-01 -2.624e-02 +#> 50 parent 0.63 7.162e-01 -8.624e-02 +#> 75 parent 0.05 6.074e-02 -1.074e-02 +#> 75 parent 0.06 6.074e-02 -7.381e-04 +#> 100 parent NA 5.151e-03 NA +#> 100 parent NA 5.151e-03 NA +#> 120 parent NA 7.155e-04 NA +#> 120 parent NA 7.155e-04 NA +#> 0 m1 0.00 0.000e+00 0.000e+00 +#> 0 m1 0.00 0.000e+00 0.000e+00 +#> 1 m1 4.84 4.803e+00 3.704e-02 +#> 1 m1 5.64 4.803e+00 8.370e-01 +#> 3 m1 12.91 1.302e+01 -1.140e-01 +#> 3 m1 12.96 1.302e+01 -6.400e-02 +#> 7 m1 22.97 2.504e+01 -2.075e+00 +#> 7 m1 24.47 2.504e+01 -5.748e-01 +#> 14 m1 41.69 3.669e+01 5.000e+00 +#> 14 m1 33.21 3.669e+01 -3.480e+00 +#> 21 m1 44.37 4.165e+01 2.717e+00 +#> 21 m1 46.44 4.165e+01 4.787e+00 +#> 35 m1 41.22 4.331e+01 -2.093e+00 +#> 35 m1 37.95 4.331e+01 -5.363e+00 +#> 50 m1 41.19 4.122e+01 -2.831e-02 +#> 50 m1 40.01 4.122e+01 -1.208e+00 +#> 75 m1 40.09 3.645e+01 3.643e+00 +#> 75 m1 33.85 3.645e+01 -2.597e+00 +#> 100 m1 31.04 3.198e+01 -9.416e-01 +#> 100 m1 33.13 3.198e+01 1.148e+00 +#> 120 m1 25.15 2.879e+01 -3.640e+00 +#> 120 m1 33.31 2.879e+01 4.520e+00
f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs")
#> Model cost at call 1 : 15156.12 +#> Model cost at call 2 : 15156.12 +#> Model cost at call 6 : 8243.644 +#> Model cost at call 12 : 6290.714 +#> Model cost at call 13 : 6290.684 +#> Model cost at call 15 : 6290.453 +#> Model cost at call 18 : 1700.75 +#> Model cost at call 20 : 1700.612 +#> Model cost at call 24 : 1190.923 +#> Model cost at call 26 : 1190.922 +#> Model cost at call 29 : 1017.417 +#> Model cost at call 31 : 1017.417 +#> Model cost at call 33 : 1017.416 +#> Model cost at call 34 : 644.0471 +#> Model cost at call 36 : 644.0469 +#> Model cost at call 38 : 644.0468 +#> Model cost at call 39 : 590.5024 +#> Model cost at call 41 : 590.5021 +#> Model cost at call 43 : 590.5015 +#> Model cost at call 44 : 543.2187 +#> Model cost at call 45 : 543.2183 +#> Model cost at call 46 : 543.2182 +#> Model cost at call 50 : 391.348 +#> Model cost at call 51 : 391.3479 +#> Model cost at call 56 : 386.4789 +#> Model cost at call 58 : 386.4789 +#> Model cost at call 60 : 386.4779 +#> Model cost at call 61 : 384.0686 +#> Model cost at call 63 : 384.0686 +#> Model cost at call 66 : 382.7812 +#> Model cost at call 68 : 382.7812 +#> Model cost at call 70 : 382.7812 +#> Model cost at call 71 : 378.9272 +#> Model cost at call 73 : 378.9272 +#> Model cost at call 75 : 378.9272 +#> Model cost at call 76 : 377.4846 +#> Model cost at call 78 : 377.4846 +#> Model cost at call 81 : 375.9738 +#> Model cost at call 83 : 375.9738 +#> Model cost at call 86 : 375.3387 +#> Model cost at call 88 : 375.3387 +#> Model cost at call 91 : 374.5774 +#> Model cost at call 93 : 374.5774 +#> Model cost at call 95 : 374.5774 +#> Model cost at call 96 : 373.5447 +#> Model cost at call 100 : 373.5446 +#> Model cost at call 102 : 373.2643 +#> Model cost at call 104 : 373.2643 +#> Model cost at call 107 : 372.6799 +#> Model cost at call 111 : 372.6798 +#> Model cost at call 114 : 372.6325 +#> Model cost at call 116 : 372.6325 +#> Model cost at call 119 : 372.6159 +#> Model cost at call 121 : 372.6159 +#> Model cost at call 123 : 372.6159 +#> Model cost at call 124 : 372.5845 +#> Model cost at call 126 : 372.5845 +#> Model cost at call 129 : 372.5375 +#> Model cost at call 130 : 372.4771 +#> Model cost at call 131 : 372.2008 +#> Model cost at call 132 : 371.4923 +#> Model cost at call 134 : 371.4923 +#> Model cost at call 137 : 371.3022 +#> Model cost at call 139 : 371.3022 +#> Model cost at call 143 : 371.2271 +#> Model cost at call 144 : 371.2271 +#> Model cost at call 148 : 371.2202 +#> Model cost at call 149 : 371.215 +#> Model cost at call 152 : 371.215 +#> Model cost at call 154 : 371.2136 +#> Model cost at call 155 : 371.2136 +#> Model cost at call 156 : 371.2136 +#> Model cost at call 160 : 371.2134 +#> Model cost at call 164 : 371.2134 +#> Model cost at call 167 : 371.2134 +#> IRLS based on variance estimates for each observed variable +#> Initial variance estimates are: +#> parent m1 +#> 11.552581 7.421226 +#> Model cost at call 186 : 40 +#> Model cost at call 188 : 40 +#> Model cost at call 194 : 39.99562 +#> Model cost at call 195 : 39.99562 +#> Model cost at call 201 : 39.9956 +#> Model cost at call 203 : 39.99528 +#> Model cost at call 205 : 39.99528 +#> Model cost at call 207 : 39.99528 +#> Model cost at call 209 : 39.99515 +#> Model cost at call 211 : 39.99515 +#> Model cost at call 214 : 39.99515 +#> Model cost at call 215 : 39.99505 +#> Model cost at call 217 : 39.99505 +#> Model cost at call 219 : 39.99505 +#> Model cost at call 220 : 39.99489 +#> Model cost at call 222 : 39.99489 +#> Model cost at call 224 : 39.99489 +#> Model cost at call 225 : 39.99479 +#> Model cost at call 227 : 39.99479 +#> Model cost at call 231 : 39.99467 +#> Model cost at call 234 : 39.99467 +#> Model cost at call 235 : 39.99467 +#> Model cost at call 236 : 39.99458 +#> Model cost at call 238 : 39.99458 +#> Model cost at call 239 : 39.99458 +#> Model cost at call 241 : 39.99452 +#> Model cost at call 242 : 39.99444 +#> Model cost at call 243 : 39.99433 +#> Model cost at call 245 : 39.99433 +#> Model cost at call 248 : 39.99383 +#> Model cost at call 250 : 39.99383 +#> Model cost at call 251 : 39.99383 +#> Model cost at call 252 : 39.99383 +#> Model cost at call 253 : 39.9935 +#> Model cost at call 254 : 39.99309 +#> Model cost at call 256 : 39.99309 +#> Model cost at call 261 : 39.99295 +#> Model cost at call 264 : 39.99295 +#> Model cost at call 267 : 39.99281 +#> Model cost at call 272 : 39.99281 +#> Model cost at call 273 : 39.99278 +#> Model cost at call 276 : 39.99278 +#> Model cost at call 278 : 39.99278 +#> Model cost at call 279 : 39.99278 +#> Model cost at call 281 : 39.99278 +#> Model cost at call 283 : 39.99278 +#> Model cost at call 286 : 39.99278 +#> Model cost at call 289 : 39.99278 +#> Model cost at call 290 : 39.99278 +#> Iteration 1 yields variance estimates: +#> parent m1 +#> 11.573172 7.407968 +#> Sum of squared differences to last variance estimates: 1.5e-05 +#> Iteration 2 yields variance estimates: +#> parent m1 +#> 11.573405 7.407846 +#> Sum of squared differences to last variance estimates: 1.7e-09 +#> Optimisation by method Port successfully terminated.
summary(f.irls)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:19:50 2016 +#> Date of summary: Fri Nov 18 15:19:50 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 486 model solutions performed in 2.052 s +#> +#> Weighting: none then iterative reweighting method obs +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 99.67000 1.79200 96.04000 103.300 +#> log_k_parent -2.31200 0.04560 -2.40400 -2.220 +#> log_k_m1 -5.25100 0.12510 -5.50500 -4.998 +#> f_parent_ilr_1 0.03785 0.06318 -0.09027 0.166 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.0000 0.5083 -0.1979 -0.6148 +#> log_k_parent 0.5083 1.0000 -0.3894 -0.6062 +#> log_k_m1 -0.1979 -0.3894 1.0000 0.7417 +#> f_parent_ilr_1 -0.6148 -0.6062 0.7417 1.0000 +#> +#> Residual standard error: 1.054 on 36 degrees of freedom +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 99.67000 55.630 8.183e-37 96.040000 1.033e+02 +#> k_parent 0.09906 21.930 1.016e-22 0.090310 1.087e-01 +#> k_m1 0.00524 7.996 8.487e-10 0.004066 6.753e-03 +#> f_parent_to_m1 0.51340 23.000 2.039e-23 0.468100 5.584e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.399 4 15 +#> parent 6.466 2 7 +#> m1 4.679 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5134 +#> parent_sink 0.4866 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 6.997 23.24 +#> m1 132.282 439.43 +#> +#> Data: +#> time variable observed predicted residual err +#> 0 parent 99.46 9.967e+01 -2.122e-01 3.402 +#> 0 parent 102.04 9.967e+01 2.368e+00 3.402 +#> 1 parent 93.50 9.027e+01 3.228e+00 3.402 +#> 1 parent 92.50 9.027e+01 2.228e+00 3.402 +#> 3 parent 63.23 7.405e+01 -1.082e+01 3.402 +#> 3 parent 68.99 7.405e+01 -5.056e+00 3.402 +#> 7 parent 52.32 4.982e+01 2.499e+00 3.402 +#> 7 parent 55.13 4.982e+01 5.309e+00 3.402 +#> 14 parent 27.27 2.490e+01 2.367e+00 3.402 +#> 14 parent 26.64 2.490e+01 1.737e+00 3.402 +#> 21 parent 11.50 1.245e+01 -9.477e-01 3.402 +#> 21 parent 11.64 1.245e+01 -8.077e-01 3.402 +#> 35 parent 2.85 3.110e+00 -2.600e-01 3.402 +#> 35 parent 2.91 3.110e+00 -2.000e-01 3.402 +#> 50 parent 0.69 7.037e-01 -1.375e-02 3.402 +#> 50 parent 0.63 7.037e-01 -7.375e-02 3.402 +#> 75 parent 0.05 5.913e-02 -9.134e-03 3.402 +#> 75 parent 0.06 5.913e-02 8.661e-04 3.402 +#> 100 parent NA 4.969e-03 NA 3.402 +#> 100 parent NA 4.969e-03 NA 3.402 +#> 120 parent NA 6.852e-04 NA 3.402 +#> 120 parent NA 6.852e-04 NA 3.402 +#> 0 m1 0.00 0.000e+00 0.000e+00 2.722 +#> 0 m1 0.00 0.000e+00 0.000e+00 2.722 +#> 1 m1 4.84 4.813e+00 2.672e-02 2.722 +#> 1 m1 5.64 4.813e+00 8.267e-01 2.722 +#> 3 m1 12.91 1.305e+01 -1.378e-01 2.722 +#> 3 m1 12.96 1.305e+01 -8.779e-02 2.722 +#> 7 m1 22.97 2.508e+01 -2.106e+00 2.722 +#> 7 m1 24.47 2.508e+01 -6.061e-01 2.722 +#> 14 m1 41.69 3.671e+01 4.983e+00 2.722 +#> 14 m1 33.21 3.671e+01 -3.497e+00 2.722 +#> 21 m1 44.37 4.165e+01 2.719e+00 2.722 +#> 21 m1 46.44 4.165e+01 4.789e+00 2.722 +#> 35 m1 41.22 4.329e+01 -2.069e+00 2.722 +#> 35 m1 37.95 4.329e+01 -5.339e+00 2.722 +#> 50 m1 41.19 4.119e+01 -3.388e-03 2.722 +#> 50 m1 40.01 4.119e+01 -1.183e+00 2.722 +#> 75 m1 40.09 3.644e+01 3.652e+00 2.722 +#> 75 m1 33.85 3.644e+01 -2.588e+00 2.722 +#> 100 m1 31.04 3.199e+01 -9.497e-01 2.722 +#> 100 m1 33.13 3.199e+01 1.140e+00 2.722 +#> 120 m1 25.15 2.881e+01 -3.659e+00 2.722 +#> 120 m1 33.31 2.881e+01 4.501e+00 2.722
f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean")
#> Model cost at call 1 : 19.80132 +#> Model cost at call 2 : 19.80132 +#> Model cost at call 6 : 10.68776 +#> Model cost at call 12 : 7.14353 +#> Model cost at call 13 : 7.143529 +#> Model cost at call 15 : 7.143511 +#> Model cost at call 18 : 2.189024 +#> Model cost at call 20 : 2.189019 +#> Model cost at call 23 : 1.587262 +#> Model cost at call 25 : 1.587261 +#> Model cost at call 26 : 1.58726 +#> Model cost at call 28 : 1.036794 +#> Model cost at call 29 : 1.036794 +#> Model cost at call 30 : 1.036793 +#> Model cost at call 34 : 0.4939937 +#> Model cost at call 35 : 0.4939937 +#> Model cost at call 38 : 0.4939936 +#> Model cost at call 39 : 0.4018506 +#> Model cost at call 43 : 0.4018505 +#> Model cost at call 45 : 0.3797853 +#> Model cost at call 51 : 0.3669779 +#> Model cost at call 55 : 0.3669778 +#> Model cost at call 56 : 0.3585654 +#> Model cost at call 57 : 0.3533252 +#> Model cost at call 62 : 0.3502505 +#> Model cost at call 64 : 0.3502505 +#> Model cost at call 66 : 0.3502505 +#> Model cost at call 67 : 0.3501535 +#> Model cost at call 72 : 0.3501187 +#> Model cost at call 74 : 0.3501187 +#> Model cost at call 75 : 0.3501187 +#> Model cost at call 77 : 0.3500378 +#> Model cost at call 79 : 0.3500378 +#> Model cost at call 83 : 0.349831 +#> Model cost at call 88 : 0.3494286 +#> Model cost at call 93 : 0.3488101 +#> Model cost at call 98 : 0.3481444 +#> Model cost at call 103 : 0.3478528 +#> Model cost at call 108 : 0.3478092 +#> Model cost at call 109 : 0.3478092 +#> Model cost at call 113 : 0.347807 +#> Model cost at call 116 : 0.347807 +#> Model cost at call 117 : 0.347807 +#> Model cost at call 119 : 0.347807 +#> Model cost at call 120 : 0.347807 +#> Model cost at call 125 : 0.347807 +#> Model cost at call 126 : 0.347807 +#> Model cost at call 128 : 0.347807 +#> Model cost at call 137 : 0.347807 +#> Model cost at call 148 : 0.347807 +#> Model cost at call 152 : 0.347807 +#> Model cost at call 154 : 0.347807 +#> Optimisation by method Port successfully terminated.
summary(f.w.mean)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:19:50 2016 +#> Date of summary: Fri Nov 18 15:19:50 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 155 model solutions performed in 0.636 s +#> +#> Weighting: mean +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 99.7300 1.93200 95.81000 103.6000 +#> log_k_parent -2.3090 0.04837 -2.40700 -2.2110 +#> log_k_m1 -5.2550 0.12070 -5.49900 -5.0100 +#> f_parent_ilr_1 0.0354 0.06344 -0.09327 0.1641 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.0000 0.5004 -0.2143 -0.6514 +#> log_k_parent 0.5004 1.0000 -0.4282 -0.6383 +#> log_k_m1 -0.2143 -0.4282 1.0000 0.7390 +#> f_parent_ilr_1 -0.6514 -0.6383 0.7390 1.0000 +#> +#> Residual standard error: 0.09829 on 36 degrees of freedom +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 99.730000 51.630 1.166e-35 95.81000 1.036e+02 +#> k_parent 0.099360 20.670 7.304e-22 0.09007 1.096e-01 +#> k_m1 0.005224 8.287 3.649e-10 0.00409 6.672e-03 +#> f_parent_to_m1 0.512500 22.860 2.497e-23 0.46710 5.578e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.401 4 15 +#> parent 6.473 2 7 +#> m1 4.671 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5125 +#> parent_sink 0.4875 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 6.976 23.18 +#> m1 132.696 440.81 +#> +#> Data: +#> time variable observed predicted residual +#> 0 parent 99.46 99.730570 -0.270570 +#> 0 parent 102.04 99.730570 2.309430 +#> 1 parent 93.50 90.298055 3.201945 +#> 1 parent 92.50 90.298055 2.201945 +#> 3 parent 63.23 74.025028 -10.795028 +#> 3 parent 68.99 74.025028 -5.035028 +#> 7 parent 52.32 49.748382 2.571618 +#> 7 parent 55.13 49.748382 5.381618 +#> 14 parent 27.27 24.815876 2.454124 +#> 14 parent 26.64 24.815876 1.824124 +#> 21 parent 11.50 12.378849 -0.878849 +#> 21 parent 11.64 12.378849 -0.738849 +#> 35 parent 2.85 3.080219 -0.230219 +#> 35 parent 2.91 3.080219 -0.170219 +#> 50 parent 0.69 0.693958 -0.003958 +#> 50 parent 0.63 0.693958 -0.063958 +#> 75 parent 0.05 0.057888 -0.007888 +#> 75 parent 0.06 0.057888 0.002112 +#> 100 parent NA 0.004829 NA +#> 100 parent NA 0.004829 NA +#> 120 parent NA 0.000662 NA +#> 120 parent NA 0.000662 NA +#> 0 m1 0.00 0.000000 0.000000 +#> 0 m1 0.00 0.000000 0.000000 +#> 1 m1 4.84 4.821488 0.018512 +#> 1 m1 5.64 4.821488 0.818512 +#> 3 m1 12.91 13.066692 -0.156692 +#> 3 m1 12.96 13.066692 -0.106692 +#> 7 m1 22.97 25.101058 -2.131058 +#> 7 m1 24.47 25.101058 -0.631058 +#> 14 m1 41.69 36.720923 4.969077 +#> 14 m1 33.21 36.720923 -3.510923 +#> 21 m1 44.37 41.648353 2.721647 +#> 21 m1 46.44 41.648353 4.791647 +#> 35 m1 41.22 43.269225 -2.049225 +#> 35 m1 37.95 43.269225 -5.319225 +#> 50 m1 41.19 41.173639 0.016361 +#> 50 m1 40.01 41.173639 -1.163639 +#> 75 m1 40.09 36.431224 3.658776 +#> 75 m1 33.85 36.431224 -2.581224 +#> 100 m1 31.04 31.996124 -0.956124 +#> 100 m1 33.13 31.996124 1.133876 +#> 120 m1 25.15 28.824128 -3.674128 +#> 120 m1 33.31 28.824128 4.485872
f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value")
#> Model cost at call 1 : 11.21571 +#> Model cost at call 2 : 11.21571 +#> Model cost at call 3 : 11.21571 +#> Model cost at call 8 : 11.12803 +#> Model cost at call 10 : 11.128 +#> Model cost at call 13 : 10.88016 +#> Model cost at call 15 : 10.88016 +#> Model cost at call 18 : 10.58819 +#> Model cost at call 20 : 10.58819 +#> Model cost at call 23 : 9.71699 +#> Model cost at call 24 : 7.794026 +#> Model cost at call 26 : 7.794026 +#> Model cost at call 31 : 6.89734 +#> Model cost at call 33 : 6.897337 +#> Model cost at call 36 : 5.2239 +#> Model cost at call 37 : 3.357735 +#> Model cost at call 41 : 3.357733 +#> Model cost at call 44 : 2.982323 +#> Model cost at call 46 : 2.982322 +#> Model cost at call 49 : 2.703946 +#> Model cost at call 50 : 2.080395 +#> Model cost at call 55 : 0.5307591 +#> Model cost at call 56 : 0.5307591 +#> Model cost at call 57 : 0.5307591 +#> Model cost at call 59 : 0.5307584 +#> Model cost at call 60 : 0.3240066 +#> Model cost at call 61 : 0.3240066 +#> Model cost at call 64 : 0.3240066 +#> Model cost at call 65 : 0.2601108 +#> Model cost at call 70 : 0.2414055 +#> Model cost at call 74 : 0.2414055 +#> Model cost at call 75 : 0.2404251 +#> Model cost at call 80 : 0.2404087 +#> Model cost at call 82 : 0.2404087 +#> Model cost at call 85 : 0.2404054 +#> Model cost at call 88 : 0.2404054 +#> Model cost at call 92 : 0.2403931 +#> Model cost at call 93 : 0.2403784 +#> Model cost at call 98 : 0.2403784 +#> Model cost at call 99 : 0.2403322 +#> Model cost at call 104 : 0.2402188 +#> Model cost at call 109 : 0.2400275 +#> Model cost at call 114 : 0.239844 +#> Model cost at call 119 : 0.2397153 +#> Model cost at call 120 : 0.2397153 +#> Model cost at call 124 : 0.2396978 +#> Model cost at call 126 : 0.2396978 +#> Model cost at call 130 : 0.239697 +#> Model cost at call 131 : 0.2396963 +#> Model cost at call 133 : 0.2396963 +#> Model cost at call 138 : 0.2396962 +#> Model cost at call 139 : 0.2396962 +#> Model cost at call 141 : 0.2396962 +#> Model cost at call 144 : 0.2396962 +#> Model cost at call 147 : 0.2396962 +#> Model cost at call 156 : 0.2396962 +#> Model cost at call 167 : 0.2396962 +#> Model cost at call 169 : 0.2396962 +#> Optimisation by method Port successfully terminated.
summary(f.w.value)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:19:51 2016 +#> Date of summary: Fri Nov 18 15:19:51 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 174 model solutions performed in 0.789 s +#> +#> Weighting: manual +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 99.6600 2.712000 94.14000 105.2000 +#> log_k_parent -2.2980 0.008118 -2.31500 -2.2820 +#> log_k_m1 -5.2410 0.096690 -5.43800 -5.0450 +#> f_parent_ilr_1 0.0231 0.057990 -0.09474 0.1409 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.00000 0.6844 -0.08687 -0.7564 +#> log_k_parent 0.68435 1.0000 -0.12694 -0.5812 +#> log_k_m1 -0.08687 -0.1269 1.00000 0.5195 +#> f_parent_ilr_1 -0.75644 -0.5812 0.51951 1.0000 +#> +#> Residual standard error: 0.08396 on 34 degrees of freedom +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 99.660000 36.75 2.957e-29 94.14000 1.052e+02 +#> k_parent 0.100400 123.20 5.927e-47 0.09878 1.021e-01 +#> k_m1 0.005295 10.34 2.447e-12 0.00435 6.444e-03 +#> f_parent_to_m1 0.508200 24.79 1.184e-23 0.46660 5.497e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.461 4 15 +#> parent 6.520 2 7 +#> m1 4.744 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5082 +#> parent_sink 0.4918 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 6.902 22.93 +#> m1 130.916 434.89 +#> +#> Data: +#> time variable observed predicted residual err +#> 0 parent 99.46 99.65571 -0.195714 99.46 +#> 0 parent 102.04 99.65571 2.384286 102.04 +#> 1 parent 93.50 90.13383 3.366170 93.50 +#> 1 parent 92.50 90.13383 2.366170 92.50 +#> 3 parent 63.23 73.73252 -10.502518 63.23 +#> 3 parent 68.99 73.73252 -4.742518 68.99 +#> 7 parent 52.32 49.34027 2.979728 52.32 +#> 7 parent 55.13 49.34027 5.789728 55.13 +#> 14 parent 27.27 24.42873 2.841271 27.27 +#> 14 parent 26.64 24.42873 2.211271 26.64 +#> 21 parent 11.50 12.09484 -0.594842 11.50 +#> 21 parent 11.64 12.09484 -0.454842 11.64 +#> 35 parent 2.85 2.96482 -0.114824 2.85 +#> 35 parent 2.91 2.96482 -0.054824 2.91 +#> 50 parent 0.69 0.65733 0.032670 0.69 +#> 50 parent 0.63 0.65733 -0.027330 0.63 +#> 75 parent 0.05 0.05339 -0.003386 0.05 +#> 75 parent 0.06 0.05339 0.006614 0.06 +#> 1 m1 4.84 4.82570 0.014301 4.84 +#> 1 m1 5.64 4.82570 0.814301 5.64 +#> 3 m1 12.91 13.06402 -0.154020 12.91 +#> 3 m1 12.96 13.06402 -0.104020 12.96 +#> 7 m1 22.97 25.04656 -2.076564 22.97 +#> 7 m1 24.47 25.04656 -0.576564 24.47 +#> 14 m1 41.69 36.53601 5.153988 41.69 +#> 14 m1 33.21 36.53601 -3.326012 33.21 +#> 21 m1 44.37 41.34639 3.023609 44.37 +#> 21 m1 46.44 41.34639 5.093609 46.44 +#> 35 m1 41.22 42.82669 -1.606690 41.22 +#> 35 m1 37.95 42.82669 -4.876690 37.95 +#> 50 m1 41.19 40.67342 0.516578 41.19 +#> 50 m1 40.01 40.67342 -0.663422 40.01 +#> 75 m1 40.09 35.91105 4.178947 40.09 +#> 75 m1 33.85 35.91105 -2.061053 33.85 +#> 100 m1 31.04 31.48161 -0.441612 31.04 +#> 100 m1 33.13 31.48161 1.648388 33.13 +#> 120 m1 25.15 28.32018 -3.170181 25.15 +#> 120 m1 33.31 28.32018 4.989819 33.31
+ + +# Manual weighting +dw <- FOCUS_2006_D +errors <- c(parent = 2, m1 = 1) +dw$err.man <- errors[FOCUS_2006_D$name] +f.w.man <- mkinfit(SFO_SFO.ff, dw, err = "err.man")
#> Model cost at call 1 : 3949.676 +#> Model cost at call 2 : 3949.676 +#> Model cost at call 5 : 3949.676 +#> Model cost at call 6 : 2252.859 +#> Model cost at call 8 : 2252.858 +#> Model cost at call 9 : 2252.826 +#> Model cost at call 13 : 1567.343 +#> Model cost at call 14 : 1567.342 +#> Model cost at call 15 : 1567.333 +#> Model cost at call 18 : 1041.524 +#> Model cost at call 19 : 1041.522 +#> Model cost at call 24 : 840.4649 +#> Model cost at call 26 : 840.4646 +#> Model cost at call 29 : 782.303 +#> Model cost at call 31 : 782.3028 +#> Model cost at call 34 : 664.539 +#> Model cost at call 36 : 664.5389 +#> Model cost at call 40 : 615.7908 +#> Model cost at call 42 : 615.7907 +#> Model cost at call 45 : 569.5971 +#> Model cost at call 47 : 569.597 +#> Model cost at call 50 : 517.3175 +#> Model cost at call 52 : 517.3173 +#> Model cost at call 56 : 464.8158 +#> Model cost at call 58 : 464.8157 +#> Model cost at call 62 : 433.0031 +#> Model cost at call 64 : 433.003 +#> Model cost at call 67 : 423.7407 +#> Model cost at call 69 : 423.7406 +#> Model cost at call 70 : 423.7392 +#> Model cost at call 72 : 346.2781 +#> Model cost at call 74 : 346.278 +#> Model cost at call 75 : 346.2779 +#> Model cost at call 78 : 334.5399 +#> Model cost at call 80 : 334.5398 +#> Model cost at call 83 : 324.139 +#> Model cost at call 85 : 324.1389 +#> Model cost at call 88 : 319.7514 +#> Model cost at call 90 : 319.7514 +#> Model cost at call 94 : 300.9426 +#> Model cost at call 96 : 300.9425 +#> Model cost at call 100 : 295.8803 +#> Model cost at call 102 : 295.8803 +#> Model cost at call 105 : 290.3288 +#> Model cost at call 107 : 290.3287 +#> Model cost at call 111 : 284.3257 +#> Model cost at call 113 : 284.3257 +#> Model cost at call 116 : 282.3972 +#> Model cost at call 118 : 282.3972 +#> Model cost at call 122 : 273.7385 +#> Model cost at call 124 : 273.7385 +#> Model cost at call 128 : 271.8379 +#> Model cost at call 130 : 271.8379 +#> Model cost at call 133 : 270.064 +#> Model cost at call 135 : 270.064 +#> Model cost at call 138 : 268.0107 +#> Model cost at call 140 : 268.0107 +#> Model cost at call 144 : 265.6194 +#> Model cost at call 146 : 265.6194 +#> Model cost at call 148 : 265.6194 +#> Model cost at call 149 : 263.4825 +#> Model cost at call 151 : 263.4825 +#> Model cost at call 153 : 263.4824 +#> Model cost at call 154 : 262.0988 +#> Model cost at call 156 : 262.0988 +#> Model cost at call 160 : 260.7078 +#> Model cost at call 162 : 260.7078 +#> Model cost at call 165 : 259.9453 +#> Model cost at call 167 : 259.9453 +#> Model cost at call 170 : 258.9623 +#> Model cost at call 172 : 258.9623 +#> Model cost at call 174 : 258.962 +#> Model cost at call 176 : 258.0119 +#> Model cost at call 178 : 258.0119 +#> Model cost at call 180 : 258.0119 +#> Model cost at call 181 : 257.8698 +#> Model cost at call 183 : 257.8698 +#> Model cost at call 186 : 256.8608 +#> Model cost at call 188 : 256.8608 +#> Model cost at call 190 : 256.8608 +#> Model cost at call 191 : 256.2306 +#> Model cost at call 193 : 256.2306 +#> Model cost at call 195 : 256.2305 +#> Model cost at call 196 : 255.7119 +#> Model cost at call 198 : 255.7118 +#> Model cost at call 201 : 255.3323 +#> Model cost at call 203 : 255.3323 +#> Model cost at call 205 : 255.3323 +#> Model cost at call 206 : 254.6653 +#> Model cost at call 208 : 254.6653 +#> Model cost at call 211 : 254.3984 +#> Model cost at call 213 : 254.3984 +#> Model cost at call 216 : 253.3199 +#> Model cost at call 218 : 253.3199 +#> Model cost at call 220 : 253.3198 +#> Model cost at call 221 : 252.4845 +#> Model cost at call 223 : 252.4845 +#> Model cost at call 225 : 252.4845 +#> Model cost at call 226 : 251.6917 +#> Model cost at call 229 : 251.6917 +#> Model cost at call 230 : 251.6917 +#> Model cost at call 233 : 251.0189 +#> Model cost at call 235 : 251.0189 +#> Model cost at call 238 : 250.6912 +#> Model cost at call 240 : 250.6912 +#> Model cost at call 243 : 250.5546 +#> Model cost at call 245 : 250.5546 +#> Model cost at call 248 : 250.466 +#> Model cost at call 249 : 250.3744 +#> Model cost at call 250 : 249.9681 +#> Model cost at call 251 : 249.2215 +#> Model cost at call 260 : 248.919 +#> Model cost at call 264 : 248.919 +#> Model cost at call 265 : 248.8876 +#> Model cost at call 267 : 248.8876 +#> Model cost at call 270 : 248.8521 +#> Model cost at call 271 : 248.8178 +#> Model cost at call 272 : 248.6837 +#> Model cost at call 273 : 248.5989 +#> Model cost at call 276 : 248.5989 +#> Model cost at call 278 : 248.5935 +#> Model cost at call 280 : 248.5935 +#> Model cost at call 282 : 248.5935 +#> Model cost at call 283 : 248.5902 +#> Model cost at call 284 : 248.5902 +#> Model cost at call 289 : 248.5902 +#> Model cost at call 298 : 248.5902 +#> Model cost at call 309 : 248.5902 +#> Model cost at call 311 : 248.5902 +#> Optimisation by method Port successfully terminated.
summary(f.w.man)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:19:53 2016 +#> Date of summary: Fri Nov 18 15:19:53 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 316 model solutions performed in 1.337 s +#> +#> Weighting: manual +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 99.49000 1.33200 96.7800 102.2000 +#> log_k_parent -2.32100 0.03550 -2.3930 -2.2490 +#> log_k_m1 -5.24100 0.21280 -5.6730 -4.8100 +#> f_parent_ilr_1 0.04571 0.08966 -0.1361 0.2275 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.00000 0.5312 -0.09455 -0.3351 +#> log_k_parent 0.53123 1.0000 -0.17800 -0.3360 +#> log_k_m1 -0.09455 -0.1780 1.00000 0.7616 +#> f_parent_ilr_1 -0.33513 -0.3360 0.76156 1.0000 +#> +#> Residual standard error: 2.628 on 36 degrees of freedom +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 99.490000 74.69 2.222e-41 96.780000 1.022e+02 +#> k_parent 0.098140 28.17 2.012e-26 0.091320 1.055e-01 +#> k_m1 0.005292 4.70 1.873e-05 0.003437 8.148e-03 +#> f_parent_to_m1 0.516200 16.30 1.686e-18 0.452000 5.798e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.400 4 15 +#> parent 6.454 2 7 +#> m1 4.708 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5162 +#> parent_sink 0.4838 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 7.063 23.46 +#> m1 130.971 435.08 +#> +#> Data: +#> time variable observed predicted residual err +#> 0 parent 99.46 99.485977 -0.025977 1 +#> 0 parent 102.04 99.485977 2.554023 1 +#> 1 parent 93.50 90.186118 3.313882 1 +#> 1 parent 92.50 90.186118 2.313882 1 +#> 3 parent 63.23 74.113162 -10.883162 1 +#> 3 parent 68.99 74.113162 -5.123162 1 +#> 7 parent 52.32 50.050295 2.269705 1 +#> 7 parent 55.13 50.050295 5.079705 1 +#> 14 parent 27.27 25.179750 2.090250 1 +#> 14 parent 26.64 25.179750 1.460250 1 +#> 21 parent 11.50 12.667654 -1.167654 1 +#> 21 parent 11.64 12.667654 -1.027654 1 +#> 35 parent 2.85 3.206164 -0.356164 1 +#> 35 parent 2.91 3.206164 -0.296164 1 +#> 50 parent 0.69 0.735619 -0.045619 1 +#> 50 parent 0.63 0.735619 -0.105619 1 +#> 75 parent 0.05 0.063256 -0.013256 1 +#> 75 parent 0.06 0.063256 -0.003256 1 +#> 100 parent NA 0.005439 NA 1 +#> 100 parent NA 0.005439 NA 1 +#> 120 parent NA 0.000764 NA 1 +#> 120 parent NA 0.000764 NA 1 +#> 0 m1 0.00 0.000000 0.000000 2 +#> 0 m1 0.00 0.000000 0.000000 2 +#> 1 m1 4.84 4.787287 0.052713 2 +#> 1 m1 5.64 4.787287 0.852713 2 +#> 3 m1 12.91 12.987848 -0.077848 2 +#> 3 m1 12.96 12.987848 -0.027848 2 +#> 7 m1 22.97 24.996945 -2.026945 2 +#> 7 m1 24.47 24.996945 -0.526945 2 +#> 14 m1 41.69 36.663527 5.026473 2 +#> 14 m1 33.21 36.663527 -3.453527 2 +#> 21 m1 44.37 41.656812 2.713188 2 +#> 21 m1 46.44 41.656812 4.783188 2 +#> 35 m1 41.22 43.350311 -2.130311 2 +#> 35 m1 37.95 43.350311 -5.400311 2 +#> 50 m1 41.19 41.256364 -0.066364 2 +#> 50 m1 40.01 41.256364 -1.246364 2 +#> 75 m1 40.09 36.460566 3.629434 2 +#> 75 m1 33.85 36.460566 -2.610566 2 +#> 100 m1 31.04 31.969288 -0.929288 2 +#> 100 m1 33.13 31.969288 1.160712 2 +#> 120 m1 25.15 28.760615 -3.610615 2 +#> 120 m1 33.31 28.760615 4.549385 2
f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", + reweight.method = "obs")
#> Model cost at call 1 : 3949.676 +#> Model cost at call 2 : 3949.676 +#> Model cost at call 5 : 3949.676 +#> Model cost at call 6 : 2252.859 +#> Model cost at call 8 : 2252.858 +#> Model cost at call 9 : 2252.826 +#> Model cost at call 13 : 1567.343 +#> Model cost at call 14 : 1567.342 +#> Model cost at call 15 : 1567.333 +#> Model cost at call 18 : 1041.524 +#> Model cost at call 19 : 1041.522 +#> Model cost at call 24 : 840.4649 +#> Model cost at call 26 : 840.4646 +#> Model cost at call 29 : 782.303 +#> Model cost at call 31 : 782.3028 +#> Model cost at call 34 : 664.539 +#> Model cost at call 36 : 664.5389 +#> Model cost at call 40 : 615.7908 +#> Model cost at call 42 : 615.7907 +#> Model cost at call 45 : 569.5971 +#> Model cost at call 47 : 569.597 +#> Model cost at call 50 : 517.3175 +#> Model cost at call 52 : 517.3173 +#> Model cost at call 56 : 464.8158 +#> Model cost at call 58 : 464.8157 +#> Model cost at call 62 : 433.0031 +#> Model cost at call 64 : 433.003 +#> Model cost at call 67 : 423.7407 +#> Model cost at call 69 : 423.7406 +#> Model cost at call 70 : 423.7392 +#> Model cost at call 72 : 346.2781 +#> Model cost at call 74 : 346.278 +#> Model cost at call 75 : 346.2779 +#> Model cost at call 78 : 334.5399 +#> Model cost at call 80 : 334.5398 +#> Model cost at call 83 : 324.139 +#> Model cost at call 85 : 324.1389 +#> Model cost at call 88 : 319.7514 +#> Model cost at call 90 : 319.7514 +#> Model cost at call 94 : 300.9426 +#> Model cost at call 96 : 300.9425 +#> Model cost at call 100 : 295.8803 +#> Model cost at call 102 : 295.8803 +#> Model cost at call 105 : 290.3288 +#> Model cost at call 107 : 290.3287 +#> Model cost at call 111 : 284.3257 +#> Model cost at call 113 : 284.3257 +#> Model cost at call 116 : 282.3972 +#> Model cost at call 118 : 282.3972 +#> Model cost at call 122 : 273.7385 +#> Model cost at call 124 : 273.7385 +#> Model cost at call 128 : 271.8379 +#> Model cost at call 130 : 271.8379 +#> Model cost at call 133 : 270.064 +#> Model cost at call 135 : 270.064 +#> Model cost at call 138 : 268.0107 +#> Model cost at call 140 : 268.0107 +#> Model cost at call 144 : 265.6194 +#> Model cost at call 146 : 265.6194 +#> Model cost at call 148 : 265.6194 +#> Model cost at call 149 : 263.4825 +#> Model cost at call 151 : 263.4825 +#> Model cost at call 153 : 263.4824 +#> Model cost at call 154 : 262.0988 +#> Model cost at call 156 : 262.0988 +#> Model cost at call 160 : 260.7078 +#> Model cost at call 162 : 260.7078 +#> Model cost at call 165 : 259.9453 +#> Model cost at call 167 : 259.9453 +#> Model cost at call 170 : 258.9623 +#> Model cost at call 172 : 258.9623 +#> Model cost at call 174 : 258.962 +#> Model cost at call 176 : 258.0119 +#> Model cost at call 178 : 258.0119 +#> Model cost at call 180 : 258.0119 +#> Model cost at call 181 : 257.8698 +#> Model cost at call 183 : 257.8698 +#> Model cost at call 186 : 256.8608 +#> Model cost at call 188 : 256.8608 +#> Model cost at call 190 : 256.8608 +#> Model cost at call 191 : 256.2306 +#> Model cost at call 193 : 256.2306 +#> Model cost at call 195 : 256.2305 +#> Model cost at call 196 : 255.7119 +#> Model cost at call 198 : 255.7118 +#> Model cost at call 201 : 255.3323 +#> Model cost at call 203 : 255.3323 +#> Model cost at call 205 : 255.3323 +#> Model cost at call 206 : 254.6653 +#> Model cost at call 208 : 254.6653 +#> Model cost at call 211 : 254.3984 +#> Model cost at call 213 : 254.3984 +#> Model cost at call 216 : 253.3199 +#> Model cost at call 218 : 253.3199 +#> Model cost at call 220 : 253.3198 +#> Model cost at call 221 : 252.4845 +#> Model cost at call 223 : 252.4845 +#> Model cost at call 225 : 252.4845 +#> Model cost at call 226 : 251.6917 +#> Model cost at call 229 : 251.6917 +#> Model cost at call 230 : 251.6917 +#> Model cost at call 233 : 251.0189 +#> Model cost at call 235 : 251.0189 +#> Model cost at call 238 : 250.6912 +#> Model cost at call 240 : 250.6912 +#> Model cost at call 243 : 250.5546 +#> Model cost at call 245 : 250.5546 +#> Model cost at call 248 : 250.466 +#> Model cost at call 249 : 250.3744 +#> Model cost at call 250 : 249.9681 +#> Model cost at call 251 : 249.2215 +#> Model cost at call 260 : 248.919 +#> Model cost at call 264 : 248.919 +#> Model cost at call 265 : 248.8876 +#> Model cost at call 267 : 248.8876 +#> Model cost at call 270 : 248.8521 +#> Model cost at call 271 : 248.8178 +#> Model cost at call 272 : 248.6837 +#> Model cost at call 273 : 248.5989 +#> Model cost at call 276 : 248.5989 +#> Model cost at call 278 : 248.5935 +#> Model cost at call 280 : 248.5935 +#> Model cost at call 282 : 248.5935 +#> Model cost at call 283 : 248.5902 +#> Model cost at call 284 : 248.5902 +#> Model cost at call 289 : 248.5902 +#> Model cost at call 298 : 248.5902 +#> Model cost at call 309 : 248.5902 +#> Model cost at call 311 : 248.5902 +#> IRLS based on variance estimates for each observed variable +#> Initial variance estimates are: +#> parent m1 +#> 11.536305 7.443046 +#> Model cost at call 317 : 40 +#> Model cost at call 319 : 40 +#> Model cost at call 324 : 39.98891 +#> Model cost at call 325 : 39.9889 +#> Model cost at call 327 : 39.98886 +#> Model cost at call 331 : 39.98871 +#> Model cost at call 333 : 39.97254 +#> Model cost at call 336 : 39.97253 +#> Model cost at call 338 : 39.96929 +#> Model cost at call 340 : 39.96929 +#> Model cost at call 344 : 39.96849 +#> Model cost at call 346 : 39.96849 +#> Model cost at call 348 : 39.96849 +#> Model cost at call 349 : 39.96774 +#> Model cost at call 351 : 39.96774 +#> Model cost at call 353 : 39.96774 +#> Model cost at call 354 : 39.96714 +#> Model cost at call 356 : 39.96714 +#> Model cost at call 359 : 39.96617 +#> Model cost at call 361 : 39.96617 +#> Model cost at call 364 : 39.96606 +#> Model cost at call 366 : 39.96606 +#> Model cost at call 369 : 39.96551 +#> Model cost at call 371 : 39.96551 +#> Model cost at call 372 : 39.96551 +#> Model cost at call 375 : 39.96527 +#> Model cost at call 378 : 39.96527 +#> Model cost at call 379 : 39.96527 +#> Model cost at call 380 : 39.96525 +#> Model cost at call 382 : 39.96525 +#> Model cost at call 385 : 39.9651 +#> Model cost at call 387 : 39.9651 +#> Model cost at call 388 : 39.9651 +#> Model cost at call 390 : 39.96502 +#> Model cost at call 393 : 39.96502 +#> Model cost at call 396 : 39.96502 +#> Model cost at call 397 : 39.96467 +#> Model cost at call 398 : 39.96422 +#> Model cost at call 399 : 39.9624 +#> Model cost at call 400 : 39.95909 +#> Model cost at call 402 : 39.95909 +#> Model cost at call 405 : 39.9571 +#> Model cost at call 407 : 39.95709 +#> Model cost at call 413 : 39.95479 +#> Model cost at call 414 : 39.95479 +#> Model cost at call 415 : 39.95479 +#> Model cost at call 417 : 39.95479 +#> Model cost at call 419 : 39.95398 +#> Model cost at call 422 : 39.95398 +#> Model cost at call 424 : 39.95387 +#> Model cost at call 429 : 39.95384 +#> Model cost at call 432 : 39.95384 +#> Model cost at call 435 : 39.95384 +#> Model cost at call 437 : 39.95384 +#> Model cost at call 438 : 39.95384 +#> Model cost at call 446 : 39.95384 +#> Model cost at call 455 : 39.95384 +#> Model cost at call 469 : 39.95384 +#> Model cost at call 473 : 39.95384 +#> Iteration 1 yields variance estimates: +#> parent m1 +#> 11.572891 7.408116 +#> Sum of squared differences to last variance estimates: 7e-05 +#> Iteration 2 yields variance estimates: +#> parent m1 +#> 11.573402 7.407847 +#> Sum of squared differences to last variance estimates: 8.1e-09 +#> Optimisation by method Port successfully terminated.
summary(f.w.man.irls)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:19:55 2016 +#> Date of summary: Fri Nov 18 15:19:55 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 648 model solutions performed in 2.716 s +#> +#> Weighting: manual then iterative reweighting method obs +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 99.67000 1.79200 96.04000 103.300 +#> log_k_parent -2.31200 0.04560 -2.40400 -2.220 +#> log_k_m1 -5.25100 0.12510 -5.50500 -4.998 +#> f_parent_ilr_1 0.03785 0.06318 -0.09027 0.166 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.0000 0.5083 -0.1979 -0.6147 +#> log_k_parent 0.5083 1.0000 -0.3894 -0.6062 +#> log_k_m1 -0.1979 -0.3894 1.0000 0.7417 +#> f_parent_ilr_1 -0.6147 -0.6062 0.7417 1.0000 +#> +#> Residual standard error: 1.054 on 36 degrees of freedom +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 99.67000 55.630 8.178e-37 96.040000 1.033e+02 +#> k_parent 0.09906 21.930 1.015e-22 0.090310 1.087e-01 +#> k_m1 0.00524 7.996 8.488e-10 0.004066 6.753e-03 +#> f_parent_to_m1 0.51340 23.000 2.038e-23 0.468100 5.584e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.399 4 15 +#> parent 6.466 2 7 +#> m1 4.679 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5134 +#> parent_sink 0.4866 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 6.997 23.24 +#> m1 132.281 439.43 +#> +#> Data: +#> time variable observed predicted residual err.ini err +#> 0 parent 99.46 9.967e+01 -2.122e-01 1 3.402 +#> 0 parent 102.04 9.967e+01 2.368e+00 1 3.402 +#> 1 parent 93.50 9.027e+01 3.228e+00 1 3.402 +#> 1 parent 92.50 9.027e+01 2.228e+00 1 3.402 +#> 3 parent 63.23 7.405e+01 -1.082e+01 1 3.402 +#> 3 parent 68.99 7.405e+01 -5.056e+00 1 3.402 +#> 7 parent 52.32 4.982e+01 2.499e+00 1 3.402 +#> 7 parent 55.13 4.982e+01 5.309e+00 1 3.402 +#> 14 parent 27.27 2.490e+01 2.367e+00 1 3.402 +#> 14 parent 26.64 2.490e+01 1.737e+00 1 3.402 +#> 21 parent 11.50 1.245e+01 -9.477e-01 1 3.402 +#> 21 parent 11.64 1.245e+01 -8.077e-01 1 3.402 +#> 35 parent 2.85 3.110e+00 -2.600e-01 1 3.402 +#> 35 parent 2.91 3.110e+00 -2.000e-01 1 3.402 +#> 50 parent 0.69 7.037e-01 -1.375e-02 1 3.402 +#> 50 parent 0.63 7.037e-01 -7.375e-02 1 3.402 +#> 75 parent 0.05 5.913e-02 -9.134e-03 1 3.402 +#> 75 parent 0.06 5.913e-02 8.659e-04 1 3.402 +#> 100 parent NA 4.969e-03 NA 1 3.402 +#> 100 parent NA 4.969e-03 NA 1 3.402 +#> 120 parent NA 6.852e-04 NA 1 3.402 +#> 120 parent NA 6.852e-04 NA 1 3.402 +#> 0 m1 0.00 0.000e+00 0.000e+00 2 2.722 +#> 0 m1 0.00 0.000e+00 0.000e+00 2 2.722 +#> 1 m1 4.84 4.813e+00 2.672e-02 2 2.722 +#> 1 m1 5.64 4.813e+00 8.267e-01 2 2.722 +#> 3 m1 12.91 1.305e+01 -1.378e-01 2 2.722 +#> 3 m1 12.96 1.305e+01 -8.778e-02 2 2.722 +#> 7 m1 22.97 2.508e+01 -2.106e+00 2 2.722 +#> 7 m1 24.47 2.508e+01 -6.061e-01 2 2.722 +#> 14 m1 41.69 3.671e+01 4.983e+00 2 2.722 +#> 14 m1 33.21 3.671e+01 -3.497e+00 2 2.722 +#> 21 m1 44.37 4.165e+01 2.719e+00 2 2.722 +#> 21 m1 46.44 4.165e+01 4.789e+00 2 2.722 +#> 35 m1 41.22 4.329e+01 -2.069e+00 2 2.722 +#> 35 m1 37.95 4.329e+01 -5.339e+00 2 2.722 +#> 50 m1 41.19 4.119e+01 -3.394e-03 2 2.722 +#> 50 m1 40.01 4.119e+01 -1.183e+00 2 2.722 +#> 75 m1 40.09 3.644e+01 3.652e+00 2 2.722 +#> 75 m1 33.85 3.644e+01 -2.588e+00 2 2.722 +#> 100 m1 31.04 3.199e+01 -9.497e-01 2 2.722 +#> 100 m1 33.13 3.199e+01 1.140e+00 2 2.722 +#> 120 m1 25.15 2.881e+01 -3.659e+00 2 2.722 +#> 120 m1 33.31 2.881e+01 4.501e+00 2 2.722
+