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/Extract.mmkin.html | 24 +- docs/reference/SFO.solution-2.png | Bin 0 -> 6424 bytes docs/reference/SFO.solution.html | 2 +- docs/reference/SFORB.solution-2.png | Bin 0 -> 6788 bytes docs/reference/SFORB.solution.html | 2 +- docs/reference/index.html | 91 +- docs/reference/mccall81_245T.html | 250 ++- docs/reference/mkinfit.html | 2169 ++++++++++++++++++++++++++- docs/reference/mkinmod.html | 62 +- docs/reference/mkinpredict.html | 6 +- docs/reference/mmkin-14.png | Bin 0 -> 30013 bytes docs/reference/mmkin-16.png | Bin 0 -> 27062 bytes docs/reference/mmkin-18.png | Bin 0 -> 25359 bytes docs/reference/mmkin-20.png | Bin 0 -> 18905 bytes docs/reference/mmkin-22.png | Bin 0 -> 17036 bytes docs/reference/mmkin.html | 1129 +++++++++++++- docs/reference/schaefer07_complex_case.html | 1054 ++++++++++++- docs/reference/summary.mkinfit.html | 6 +- docs/reference/synthetic_data_for_UBA.html | 872 ++++++++++- docs/reference/transform_odeparms.html | 527 ++++++- 20 files changed, 5957 insertions(+), 237 deletions(-) create mode 100644 docs/reference/SFO.solution-2.png create mode 100644 docs/reference/SFORB.solution-2.png create mode 100644 docs/reference/mmkin-14.png create mode 100644 docs/reference/mmkin-16.png create mode 100644 docs/reference/mmkin-18.png create mode 100644 docs/reference/mmkin-20.png create mode 100644 docs/reference/mmkin-22.png (limited to 'docs/reference') diff --git a/docs/reference/Extract.mmkin.html b/docs/reference/Extract.mmkin.html index b437fc7d..09d7513c 100644 --- a/docs/reference/Extract.mmkin.html +++ b/docs/reference/Extract.mmkin.html @@ -193,7 +193,7 @@ #> #> $time #> user system elapsed -#> 0.268 0.000 0.267 +#> 0.256 0.000 0.255 #> #> $mkinmod #> <mkinmod> model generated with @@ -379,7 +379,7 @@ #> } #> return(mC) #> } -#> <environment: 0x3a2f9e8> +#> <environment: 0x3fc5fa0> #> #> $cost_notrans #> function (P) @@ -401,7 +401,7 @@ #> scaleVar = scaleVar) #> return(mC) #> } -#> <environment: 0x3a2f9e8> +#> <environment: 0x3fc5fa0> #> #> $hessian_notrans #> parent_0 alpha beta @@ -467,7 +467,7 @@ #> 99.66619 #> #> $date -#> [1] "Thu Nov 17 22:56:49 2016" +#> [1] "Fri Nov 18 15:19:25 2016" #> #> attr(,"class") #> [1] "mkinfit" "modFit"
fits["SFO", "B"]
#> dataset @@ -546,7 +546,7 @@ #> #> $time #> user system elapsed -#> 0.116 0.000 0.115 +#> 0.064 0.000 0.066 #> #> $mkinmod #> <mkinmod> model generated with @@ -733,7 +733,7 @@ #> } #> return(mC) #> } -#> <environment: 0x42fb560> +#> <environment: 0x3b66828> #> #> $cost_notrans #> function (P) @@ -755,7 +755,7 @@ #> scaleVar = scaleVar) #> return(mC) #> } -#> <environment: 0x42fb560> +#> <environment: 0x3b66828> #> #> $hessian_notrans #> parent_0 k_parent_sink @@ -818,7 +818,7 @@ #> 99.17407 #> #> $date -#> [1] "Thu Nov 17 22:56:48 2016" +#> [1] "Fri Nov 18 15:19:25 2016" #> #> attr(,"class") #> [1] "mkinfit" "modFit"
fits["SFO", "B", drop = TRUE]
#> [[1]] @@ -894,7 +894,7 @@ #> #> $time #> user system elapsed -#> 0.116 0.000 0.115 +#> 0.064 0.000 0.066 #> #> $mkinmod #> <mkinmod> model generated with @@ -1081,7 +1081,7 @@ #> } #> return(mC) #> } -#> <environment: 0x42fb560> +#> <environment: 0x3b66828> #> #> $cost_notrans #> function (P) @@ -1103,7 +1103,7 @@ #> scaleVar = scaleVar) #> return(mC) #> } -#> <environment: 0x42fb560> +#> <environment: 0x3b66828> #> #> $hessian_notrans #> parent_0 k_parent_sink @@ -1166,7 +1166,7 @@ #> 99.17407 #> #> $date -#> [1] "Thu Nov 17 22:56:48 2016" +#> [1] "Fri Nov 18 15:19:25 2016" #> #> attr(,"class") #> [1] "mkinfit" "modFit" diff --git a/docs/reference/SFO.solution-2.png b/docs/reference/SFO.solution-2.png new file mode 100644 index 00000000..78c083c3 Binary files /dev/null and b/docs/reference/SFO.solution-2.png differ diff --git a/docs/reference/SFO.solution.html b/docs/reference/SFO.solution.html index 2ead8f24..30d7acdf 100644 --- a/docs/reference/SFO.solution.html +++ b/docs/reference/SFO.solution.html @@ -110,7 +110,7 @@

Examples

- 
  ## Not run: plot(function(x) SFO.solution(x, 100, 3), 0, 2)
+ 
  plot(function(x) SFO.solution(x, 100, 3), 0, 2)
#> 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
+
#> Successfully compiled differential equation model from auto-generated C code.
-## Not run: ------------------------------------ -# # The above model used to be specified like this, before the advent of mkinsub() -# SFO_SFO <- mkinmod( -# parent = list(type = "SFO", to = "m1"), -# m1 = list(type = "SFO")) -# -# # Show details of creating the C function -# SFO_SFO <- mkinmod( -# parent = mkinsub("SFO", "m1"), -# m1 = mkinsub("SFO"), verbose = TRUE) -# -# # If we have several parallel metabolites -# # (compare tests/testthat/test_synthetic_data_for_UBA_2014.R) -# m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")), -# M1 = mkinsub("SFO"), -# M2 = mkinsub("SFO"), -# use_of_ff = "max", quiet = TRUE) -# -# fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par, -# synthetic_data_for_UBA_2014[[12]]$data, -# quiet = TRUE) -## ---------------------------------------------
+ +# The above model used to be specified like this, before the advent of mkinsub() +SFO_SFO <- mkinmod( + parent = list(type = "SFO", to = "m1"), + m1 = list(type = "SFO"))
#> Successfully compiled differential equation model from auto-generated C code.
+# Show details of creating the C function +SFO_SFO <- mkinmod( + parent = mkinsub("SFO", "m1"), + m1 = mkinsub("SFO"), verbose = TRUE)
#> Compilation argument: +#> /usr/lib/R/bin/R CMD SHLIB file21efdcf882f.c 2> file21efdcf882f.c.err.txt +#> Program source: +#> 1: #include <R.h> +#> 2: +#> 3: +#> 4: static double parms [3]; +#> 5: #define k_parent_sink parms[0] +#> 6: #define k_parent_m1 parms[1] +#> 7: #define k_m1_sink parms[2] +#> 8: +#> 9: void initpar(void (* odeparms)(int *, double *)) { +#> 10: int N = 3; +#> 11: odeparms(&N, parms); +#> 12: } +#> 13: +#> 14: +#> 15: void func ( int * n, double * t, double * y, double * f, double * rpar, int * ipar ) { +#> 16: +#> 17: f[0] = - k_parent_sink * y[0] - k_parent_m1 * y[0]; +#> 18: f[1] = + k_parent_m1 * y[0] - k_m1_sink * y[1]; +#> 19: }
#> Successfully compiled differential equation model from auto-generated C code.
+# If we have several parallel metabolites +# (compare tests/testthat/test_synthetic_data_for_UBA_2014.R) +m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")), + M1 = mkinsub("SFO"), + M2 = mkinsub("SFO"), + use_of_ff = "max", quiet = TRUE) + +fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par, + synthetic_data_for_UBA_2014[[12]]$data, + quiet = TRUE)
#> time parent m1 #> 201 20 4.978707 27.46227
#> user system elapsed -#> 0.024 0.004 0.004
system.time( +#> 0.008 0.024 0.004
system.time( print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01), c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "deSolve")[201,]))
#> time parent m1 #> 201 20 4.978707 27.46227
#> user system elapsed -#> 0.016 0.004 0.003
system.time( +#> 0.020 0.000 0.002
system.time( print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01), c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "deSolve", use_compiled = FALSE)[201,]))
#> time parent m1 #> 201 20 4.978707 27.46227
#> user system elapsed -#> 0.032 0.000 0.035
+#> 0.032 0.000 0.034
#> Successfully compiled differential equation model from auto-generated C code.
## Not run: mkinfit(model, data, plot=TRUE)
+ A2 = list(type = "SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
mkinfit(model, data)
#> Model cost at call 1 : 2511.655 +#> Model cost at call 2 : 2511.655 +#> Model cost at call 11 : 1436.639 +#> Model cost at call 12 : 1436.638 +#> Model cost at call 13 : 1436.566 +#> Model cost at call 21 : 643.6583 +#> Model cost at call 22 : 643.6583 +#> Model cost at call 23 : 643.6582 +#> Model cost at call 29 : 643.6576 +#> Model cost at call 31 : 454.0244 +#> Model cost at call 32 : 454.0241 +#> Model cost at call 34 : 454.0229 +#> Model cost at call 43 : 378.1144 +#> Model cost at call 45 : 378.1143 +#> Model cost at call 53 : 357.245 +#> Model cost at call 55 : 357.2449 +#> Model cost at call 56 : 357.2447 +#> Model cost at call 63 : 354.3415 +#> Model cost at call 64 : 354.3415 +#> Model cost at call 65 : 354.3413 +#> Model cost at call 73 : 332.49 +#> Model cost at call 74 : 332.49 +#> Model cost at call 81 : 332.4899 +#> Model cost at call 83 : 315.2962 +#> Model cost at call 84 : 306.3085 +#> Model cost at call 86 : 306.3084 +#> Model cost at call 87 : 306.3084 +#> Model cost at call 92 : 306.3083 +#> Model cost at call 94 : 290.6377 +#> Model cost at call 96 : 290.6375 +#> Model cost at call 98 : 290.6375 +#> Model cost at call 101 : 290.6371 +#> Model cost at call 105 : 269.09 +#> Model cost at call 107 : 269.0899 +#> Model cost at call 115 : 259.7551 +#> Model cost at call 120 : 259.7549 +#> Model cost at call 123 : 259.7547 +#> Model cost at call 126 : 253.7973 +#> Model cost at call 128 : 253.7972 +#> Model cost at call 137 : 251.7358 +#> Model cost at call 139 : 251.7358 +#> Model cost at call 147 : 250.7394 +#> Model cost at call 149 : 250.7393 +#> Model cost at call 157 : 249.1148 +#> Model cost at call 159 : 249.1148 +#> Model cost at call 167 : 246.8768 +#> Model cost at call 169 : 246.8768 +#> Model cost at call 177 : 244.9758 +#> Model cost at call 179 : 244.9758 +#> Model cost at call 187 : 243.2914 +#> Model cost at call 189 : 243.2914 +#> Model cost at call 190 : 243.2914 +#> Model cost at call 194 : 243.2914 +#> Model cost at call 199 : 242.9202 +#> Model cost at call 201 : 242.9202 +#> Model cost at call 202 : 242.9202 +#> Model cost at call 209 : 242.7695 +#> Model cost at call 211 : 242.7695 +#> Model cost at call 216 : 242.7695 +#> Model cost at call 219 : 242.5771 +#> Model cost at call 221 : 242.5771 +#> Model cost at call 229 : 242.4402 +#> Model cost at call 231 : 242.4402 +#> Model cost at call 239 : 242.1878 +#> Model cost at call 241 : 242.1878 +#> Model cost at call 249 : 242.0553 +#> Model cost at call 251 : 242.0553 +#> Model cost at call 256 : 242.0553 +#> Model cost at call 259 : 241.8761 +#> Model cost at call 260 : 241.7412 +#> Model cost at call 261 : 241.6954 +#> Model cost at call 264 : 241.6954 +#> Model cost at call 275 : 241.5982 +#> Model cost at call 277 : 241.5982 +#> Model cost at call 285 : 241.5459 +#> Model cost at call 287 : 241.5459 +#> Model cost at call 295 : 241.4837 +#> Model cost at call 297 : 241.4837 +#> Model cost at call 305 : 241.3882 +#> Model cost at call 306 : 241.3161 +#> Model cost at call 307 : 241.2315 +#> Model cost at call 309 : 241.2315 +#> Model cost at call 314 : 241.2315 +#> Model cost at call 317 : 240.9738 +#> Model cost at call 322 : 240.9738 +#> Model cost at call 327 : 240.8244 +#> Model cost at call 329 : 240.8244 +#> Model cost at call 337 : 240.7005 +#> Model cost at call 339 : 240.7005 +#> Model cost at call 342 : 240.7005 +#> Model cost at call 347 : 240.629 +#> Model cost at call 350 : 240.629 +#> Model cost at call 357 : 240.6193 +#> Model cost at call 358 : 240.6193 +#> Model cost at call 364 : 240.6193 +#> Model cost at call 367 : 240.6193 +#> Model cost at call 369 : 240.5873 +#> Model cost at call 374 : 240.5873 +#> Model cost at call 380 : 240.578 +#> Model cost at call 382 : 240.578 +#> Model cost at call 390 : 240.5723 +#> Model cost at call 393 : 240.5723 +#> Model cost at call 403 : 240.569 +#> Model cost at call 404 : 240.569 +#> Model cost at call 413 : 240.569 +#> Model cost at call 415 : 240.5688 +#> Model cost at call 416 : 240.5688 +#> Model cost at call 417 : 240.5688 +#> Model cost at call 431 : 240.5686 +#> Model cost at call 432 : 240.5686 +#> Model cost at call 434 : 240.5686 +#> Model cost at call 443 : 240.5686 +#> Model cost at call 444 : 240.5686 +#> Model cost at call 447 : 240.5686 +#> Model cost at call 449 : 240.5686 +#> Model cost at call 450 : 240.5686 +#> Model cost at call 466 : 240.5686 +#> Model cost at call 470 : 240.5686 +#> Model cost at call 485 : 240.5686 +#> Model cost at call 509 : 240.5686 +#> Optimisation by method Port successfully terminated.
#> $par +#> parent_0 log_k_parent log_k_A1 log_k_B1 log_k_C1 +#> 91.9181598 -3.0020485 -4.2735924 -3.9846764 -2.7852180 +#> log_k_A2 f_parent_ilr_1 f_parent_ilr_2 f_A1_ilr_1 +#> -3.7166415 0.4718588 -0.3589948 -0.1477244 +#> +#> $ssr +#> [1] 240.5686 +#> +#> $convergence +#> [1] 0 +#> +#> $iterations +#> [1] 43 +#> +#> $evaluations +#> function gradient +#> 62 441 +#> +#> $counts +#> [1] "relative convergence (4)" +#> +#> $hessian +#> parent_0 log_k_parent log_k_A1 log_k_B1 +#> parent_0 7.3650812 -92.141920 -1.001134e+01 -2.432415e+00 +#> log_k_parent -92.1419204 6632.673492 -4.316240e+01 -1.320833e+01 +#> log_k_A1 -10.0113364 -43.162398 6.071628e+02 0.000000e+00 +#> log_k_B1 -2.4324147 -13.208329 0.000000e+00 1.572303e+02 +#> log_k_C1 -4.7153201 -118.288037 -5.878291e-05 -3.073041e-06 +#> log_k_A2 -0.4360727 -5.304259 -1.977980e+01 0.000000e+00 +#> f_parent_ilr_1 10.5460899 271.145438 -5.299954e+02 1.874235e+02 +#> f_parent_ilr_2 11.6409409 222.570696 -4.773816e+02 -1.159875e+02 +#> f_A1_ilr_1 0.5572072 10.374810 2.850173e+01 0.000000e+00 +#> log_k_C1 log_k_A2 f_parent_ilr_1 f_parent_ilr_2 +#> parent_0 -4.715320e+00 -4.360727e-01 10.54609 11.64094 +#> log_k_parent -1.182880e+02 -5.304259e+00 271.14544 222.57070 +#> log_k_A1 -5.878291e-05 -1.977980e+01 -529.99537 -477.38164 +#> log_k_B1 -3.073041e-06 0.000000e+00 187.42348 -115.98754 +#> log_k_C1 3.372749e+02 -2.395674e-06 56.85184 305.98862 +#> log_k_A2 -2.395674e-06 2.749192e+01 -23.08549 -20.79373 +#> f_parent_ilr_1 5.685184e+01 -2.308549e+01 1256.24941 632.09769 +#> f_parent_ilr_2 3.059886e+02 -2.079373e+01 632.09769 1250.65147 +#> f_A1_ilr_1 3.158891e-06 -3.129286e+01 29.49830 26.56991 +#> f_A1_ilr_1 +#> parent_0 5.572072e-01 +#> log_k_parent 1.037481e+01 +#> log_k_A1 2.850173e+01 +#> log_k_B1 0.000000e+00 +#> log_k_C1 3.158891e-06 +#> log_k_A2 -3.129286e+01 +#> f_parent_ilr_1 2.949830e+01 +#> f_parent_ilr_2 2.656991e+01 +#> f_A1_ilr_1 3.998554e+01 +#> +#> $residuals +#> parent parent parent parent parent parent parent +#> -1.2818402 -1.9372115 -0.5105519 3.8165318 -2.3531716 4.8043342 -2.2775432 +#> parent A1 A1 A1 A1 A1 A1 +#> -5.3608524 4.1967522 2.9032987 -1.3124875 -0.6021093 2.5092324 -1.8861396 +#> B1 B1 B1 B1 B1 C1 C1 +#> 4.3801768 5.5002481 -5.7917184 1.3852658 0.5313301 1.2796458 1.7105311 +#> C1 C1 C1 C1 C1 A2 A2 +#> 3.7116712 -0.1182953 0.5228429 -0.8570298 -3.5476556 -0.5447276 -1.3652404 +#> A2 A2 A2 A2 A2 +#> -0.3330261 -0.5802059 0.1285850 0.2119280 -0.1381990 +#> +#> $ms +#> [1] 7.289956 +#> +#> $var_ms +#> parent A1 B1 C1 A2 +#> 10.3459333 6.3301336 17.0367907 4.5639474 0.3841002 +#> +#> $var_ms_unscaled +#> parent A1 B1 C1 A2 +#> 10.3459333 6.3301336 17.0367907 4.5639474 0.3841002 +#> +#> $var_ms_unweighted +#> parent A1 B1 C1 A2 +#> 10.3459333 6.3301336 17.0367907 4.5639474 0.3841002 +#> +#> $rank +#> [1] 9 +#> +#> $df.residual +#> [1] 24 +#> +#> $solution_type +#> [1] "deSolve" +#> +#> $transform_rates +#> [1] TRUE +#> +#> $transform_fractions +#> [1] TRUE +#> +#> $method.modFit +#> [1] "Port" +#> +#> $maxit.modFit +#> [1] "auto" +#> +#> $calls +#> [1] 523 +#> +#> $time +#> user system elapsed +#> 5.004 0.000 5.004 +#> +#> $mkinmod +#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: max +#> Specification $spec: +#> $parent +#> $type: SFO; $to: A1, B1, C1; $sink: FALSE +#> $A1 +#> $type: SFO; $to: A2; $sink: TRUE +#> $B1 +#> $type: SFO; $sink: TRUE +#> $C1 +#> $type: SFO; $sink: TRUE +#> $A2 +#> $type: SFO; $sink: TRUE +#> Coefficient matrix $coefmat available +#> Compiled model $cf available +#> +#> $observed +#> name time value +#> 1 parent 0 93.20 +#> 2 parent 1 89.40 +#> 3 parent 3 79.70 +#> 4 parent 7 61.10 +#> 5 parent 14 48.20 +#> 6 parent 30 15.90 +#> 7 parent 62 6.50 +#> 8 parent 100 6.00 +#> 9 A1 0 NA +#> 10 A1 1 NA +#> 11 A1 3 0.55 +#> 12 A1 7 6.87 +#> 13 A1 14 17.08 +#> 14 A1 30 21.68 +#> 15 A1 62 15.77 +#> 16 A1 100 13.63 +#> 17 B1 0 NA +#> 18 B1 1 NA +#> 19 B1 3 NA +#> 20 B1 7 0.55 +#> 21 B1 14 2.31 +#> 22 B1 30 15.76 +#> 23 B1 62 6.36 +#> 24 B1 100 3.74 +#> 25 C1 0 NA +#> 26 C1 1 0.55 +#> 27 C1 3 3.20 +#> 28 C1 7 5.46 +#> 29 C1 14 12.55 +#> 30 C1 30 10.45 +#> 31 C1 62 4.74 +#> 32 C1 100 4.33 +#> 33 A2 0 NA +#> 34 A2 1 0.55 +#> 35 A2 3 1.41 +#> 36 A2 7 0.55 +#> 37 A2 14 1.29 +#> 38 A2 30 1.95 +#> 39 A2 62 3.54 +#> 40 A2 100 3.86 +#> +#> $obs_vars +#> [1] "parent" "A1" "B1" "C1" "A2" +#> +#> $predicted +#> name time value +#> 1 parent 0.000000 91.918159794 +#> 2 parent 1.000000 87.462788491 +#> 3 parent 1.010101 87.418904506 +#> 4 parent 2.020202 83.139880984 +#> 5 parent 3.000000 79.189448055 +#> 6 parent 3.030303 79.070309209 +#> 7 parent 4.040404 75.199936833 +#> 8 parent 5.050505 71.519013349 +#> 9 parent 6.060606 68.018265517 +#> 10 parent 7.000000 64.916531757 +#> 11 parent 7.070707 64.688874011 +#> 12 parent 8.080808 61.522451197 +#> 13 parent 9.090909 58.511020005 +#> 14 parent 10.101010 55.646993828 +#> 15 parent 11.111111 52.923157412 +#> 16 parent 12.121212 50.332648680 +#> 17 parent 13.131313 47.868941444 +#> 18 parent 14.000000 45.846828365 +#> 19 parent 14.141414 45.525828960 +#> 20 parent 15.151515 43.297408299 +#> 21 parent 16.161616 41.178065468 +#> 22 parent 17.171717 39.162461272 +#> 23 parent 18.181818 37.245517861 +#> 24 parent 19.191919 35.422405939 +#> 25 parent 20.202020 33.688532595 +#> 26 parent 21.212121 32.039529737 +#> 27 parent 22.222222 30.471243081 +#> 28 parent 23.232323 28.979721692 +#> 29 parent 24.242424 27.561208025 +#> 30 parent 25.252525 26.212128463 +#> 31 parent 26.262626 24.929084310 +#> 32 parent 27.272727 23.708843233 +#> 33 parent 28.282828 22.548331117 +#> 34 parent 29.292929 21.444624318 +#> 35 parent 30.000000 20.704334210 +#> 36 parent 30.303030 20.394942302 +#> 37 parent 31.313131 19.396640638 +#> 38 parent 32.323232 18.447204335 +#> 39 parent 33.333333 17.544241506 +#> 40 parent 34.343434 16.685477346 +#> 41 parent 35.353535 15.868748397 +#> 42 parent 36.363636 15.091997098 +#> 43 parent 37.373737 14.353266603 +#> 44 parent 38.383838 13.650695852 +#> 45 parent 39.393939 12.982514879 +#> 46 parent 40.404040 12.347040357 +#> 47 parent 41.414141 11.742671354 +#> 48 parent 42.424242 11.167885303 +#> 49 parent 43.434343 10.621234162 +#> 50 parent 44.444444 10.101340770 +#> 51 parent 45.454545 9.606895375 +#> 52 parent 46.464646 9.136652336 +#> 53 parent 47.474747 8.689426985 +#> 54 parent 48.484848 8.264092640 +#> 55 parent 49.494949 7.859577770 +#> 56 parent 50.505051 7.474863293 +#> 57 parent 51.515152 7.108980009 +#> 58 parent 52.525253 6.761006160 +#> 59 parent 53.535354 6.430065106 +#> 60 parent 54.545455 6.115323117 +#> 61 parent 55.555556 5.815987274 +#> 62 parent 56.565657 5.531303470 +#> 63 parent 57.575758 5.260554508 +#> 64 parent 58.585859 5.003058299 +#> 65 parent 59.595960 4.758166141 +#> 66 parent 60.606061 4.525261085 +#> 67 parent 61.616162 4.303756381 +#> 68 parent 62.000000 4.222456793 +#> 69 parent 62.626263 4.093093997 +#> 70 parent 63.636364 3.892743220 +#> 71 parent 64.646465 3.702199310 +#> 72 parent 65.656566 3.520982238 +#> 73 parent 66.666667 3.348635468 +#> 74 parent 67.676768 3.184724813 +#> 75 parent 68.686869 3.028837337 +#> 76 parent 69.696970 2.880580317 +#> 77 parent 70.707071 2.739580256 +#> 78 parent 71.717172 2.605481934 +#> 79 parent 72.727273 2.477947523 +#> 80 parent 73.737374 2.356655730 +#> 81 parent 74.747475 2.241300986 +#> 82 parent 75.757576 2.131592683 +#> 83 parent 76.767677 2.027254437 +#> 84 parent 77.777778 1.928023390 +#> 85 parent 78.787879 1.833649553 +#> 86 parent 79.797980 1.743895173 +#> 87 parent 80.808081 1.658534134 +#> 88 parent 81.818182 1.577351390 +#> 89 parent 82.828283 1.500142419 +#> 90 parent 83.838384 1.426712710 +#> 91 parent 84.848485 1.356877275 +#> 92 parent 85.858586 1.290460179 +#> 93 parent 86.868687 1.227294099 +#> 94 parent 87.878788 1.167219904 +#> 95 parent 88.888889 1.110086250 +#> 96 parent 89.898990 1.055749203 +#> 97 parent 90.909091 1.004071872 +#> 98 parent 91.919192 0.954924068 +#> 99 parent 92.929293 0.908181975 +#> 100 parent 93.939394 0.863727837 +#> 101 parent 94.949495 0.821449662 +#> 102 parent 95.959596 0.781240940 +#> 103 parent 96.969697 0.743000375 +#> 104 parent 97.979798 0.706631627 +#> 105 parent 98.989899 0.672043075 +#> 106 parent 100.000000 0.639147580 +#> 107 A1 0.000000 0.000000000 +#> 108 A1 1.000000 1.685461006 +#> 109 A1 1.010101 1.701940789 +#> 110 A1 2.020202 3.296791533 +#> 111 A1 3.000000 4.746752202 +#> 112 A1 3.030303 4.790126465 +#> 113 A1 4.040404 6.187242320 +#> 114 A1 5.050505 7.493171988 +#> 115 A1 6.060606 8.712697491 +#> 116 A1 7.000000 9.773298725 +#> 117 A1 7.070707 9.850362326 +#> 118 A1 8.080808 10.910483202 +#> 119 A1 9.090909 11.897161206 +#> 120 A1 10.101010 12.814292412 +#> 121 A1 11.111111 13.665577981 +#> 122 A1 12.121212 14.454533757 +#> 123 A1 13.131313 15.184499397 +#> 124 A1 14.000000 15.767512526 +#> 125 A1 14.141414 15.858647054 +#> 126 A1 15.151515 16.479989628 +#> 127 A1 16.161616 17.051388624 +#> 128 A1 17.171717 17.575561608 +#> 129 A1 18.181818 18.055089316 +#> 130 A1 19.191919 18.492422399 +#> 131 A1 20.202020 18.889887843 +#> 132 A1 21.212121 19.249695079 +#> 133 A1 22.222222 19.573941783 +#> 134 A1 23.232323 19.864619397 +#> 135 A1 24.242424 20.123618383 +#> 136 A1 25.252525 20.352733211 +#> 137 A1 26.262626 20.553667106 +#> 138 A1 27.272727 20.728036563 +#> 139 A1 28.282828 20.877375640 +#> 140 A1 29.292929 21.003140039 +#> 141 A1 30.000000 21.077890710 +#> 142 A1 30.303030 21.106710984 +#> 143 A1 31.313131 21.189398917 +#> 144 A1 32.323232 21.252447002 +#> 145 A1 33.333333 21.297034466 +#> 146 A1 34.343434 21.324279770 +#> 147 A1 35.353535 21.335243623 +#> 148 A1 36.363636 21.330931858 +#> 149 A1 37.373737 21.312298151 +#> 150 A1 38.383838 21.280246621 +#> 151 A1 39.393939 21.235634295 +#> 152 A1 40.404040 21.179273450 +#> 153 A1 41.414141 21.111933845 +#> 154 A1 42.424242 21.034344838 +#> 155 A1 43.434343 20.947197407 +#> 156 A1 44.444444 20.851146060 +#> 157 A1 45.454545 20.746810660 +#> 158 A1 46.464646 20.634778158 +#> 159 A1 47.474747 20.515604239 +#> 160 A1 48.484848 20.389814887 +#> 161 A1 49.494949 20.257907875 +#> 162 A1 50.505051 20.120354180 +#> 163 A1 51.515152 19.977599327 +#> 164 A1 52.525253 19.830064674 +#> 165 A1 53.535354 19.678148618 +#> 166 A1 54.545455 19.522227762 +#> 167 A1 55.555556 19.362658007 +#> 168 A1 56.565657 19.199775600 +#> 169 A1 57.575758 19.033898126 +#> 170 A1 58.585859 18.865325451 +#> 171 A1 59.595960 18.694340625 +#> 172 A1 60.606061 18.521210729 +#> 173 A1 61.616162 18.346187688 +#> 174 A1 62.000000 18.279232408 +#> 175 A1 62.626263 18.169509043 +#> 176 A1 63.636364 17.991398686 +#> 177 A1 64.646465 17.812067549 +#> 178 A1 65.656566 17.631714275 +#> 179 A1 66.666667 17.450525840 +#> 180 A1 67.676768 17.268678156 +#> 181 A1 68.686869 17.086336636 +#> 182 A1 69.696970 16.903656738 +#> 183 A1 70.707071 16.720784474 +#> 184 A1 71.717172 16.537856901 +#> 185 A1 72.727273 16.355002582 +#> 186 A1 73.737374 16.172342031 +#> 187 A1 74.747475 15.989988127 +#> 188 A1 75.757576 15.808046514 +#> 189 A1 76.767677 15.626615980 +#> 190 A1 77.777778 15.445788814 +#> 191 A1 78.787879 15.265651148 +#> 192 A1 79.797980 15.086283284 +#> 193 A1 80.808081 14.907759996 +#> 194 A1 81.818182 14.730150830 +#> 195 A1 82.828283 14.553520376 +#> 196 A1 83.838384 14.377928535 +#> 197 A1 84.848485 14.203430771 +#> 198 A1 85.858586 14.030078345 +#> 199 A1 86.868687 13.857918547 +#> 200 A1 87.878788 13.686994907 +#> 201 A1 88.888889 13.517347398 +#> 202 A1 89.898990 13.349012635 +#> 203 A1 90.909091 13.182024056 +#> 204 A1 91.919192 13.016412097 +#> 205 A1 92.929293 12.852204356 +#> 206 A1 93.939394 12.689425755 +#> 207 A1 94.949495 12.528098688 +#> 208 A1 95.959596 12.368243159 +#> 209 A1 96.969697 12.209876925 +#> 210 A1 97.979798 12.053015616 +#> 211 A1 98.989899 11.897672861 +#> 212 A1 100.000000 11.743860400 +#> 213 B1 0.000000 0.000000000 +#> 214 B1 1.000000 0.862762059 +#> 215 B1 1.010101 0.871177048 +#> 216 B1 2.020202 1.683497848 +#> 217 B1 3.000000 2.418226457 +#> 218 B1 3.030303 2.440145075 +#> 219 B1 4.040404 3.144139999 +#> 220 B1 5.050505 3.798350490 +#> 221 B1 6.060606 4.405498633 +#> 222 B1 7.000000 4.930176837 +#> 223 B1 7.070707 4.968167964 +#> 224 B1 8.080808 5.488810347 +#> 225 B1 9.090909 5.969752521 +#> 226 B1 10.101010 6.413202316 +#> 227 B1 11.111111 6.821254568 +#> 228 B1 12.121212 7.195896744 +#> 229 B1 13.131313 7.539014282 +#> 230 B1 14.000000 7.810248132 +#> 231 B1 14.141414 7.852395679 +#> 232 B1 15.151515 8.137737320 +#> 233 B1 16.161616 8.396648072 +#> 234 B1 17.171717 8.630653651 +#> 235 B1 18.181818 8.841200774 +#> 236 B1 19.191919 9.029661109 +#> 237 B1 20.202020 9.197335022 +#> 238 B1 21.212121 9.345455150 +#> 239 B1 22.222222 9.475189788 +#> 240 B1 23.232323 9.587646116 +#> 241 B1 24.242424 9.683873262 +#> 242 B1 25.252525 9.764865214 +#> 243 B1 26.262626 9.831563593 +#> 244 B1 27.272727 9.884860284 +#> 245 B1 28.282828 9.925599936 +#> 246 B1 29.292929 9.954582344 +#> 247 B1 30.000000 9.968281596 +#> 248 B1 30.303030 9.972564708 +#> 249 B1 31.313131 9.980263783 +#> 250 B1 32.323232 9.978357919 +#> 251 B1 33.333333 9.967489009 +#> 252 B1 34.343434 9.948264327 +#> 253 B1 35.353535 9.921258285 +#> 254 B1 36.363636 9.887014102 +#> 255 B1 37.373737 9.846045383 +#> 256 B1 38.383838 9.798837632 +#> 257 B1 39.393939 9.745849674 +#> 258 B1 40.404040 9.687515023 +#> 259 B1 41.414141 9.624243169 +#> 260 B1 42.424242 9.556420809 +#> 261 B1 43.434343 9.484413012 +#> 262 B1 44.444444 9.408564328 +#> 263 B1 45.454545 9.329199843 +#> 264 B1 46.464646 9.246626179 +#> 265 B1 47.474747 9.161132446 +#> 266 B1 48.484848 9.072991146 +#> 267 B1 49.494949 8.982459028 +#> 268 B1 50.505051 8.889777910 +#> 269 B1 51.515152 8.795175451 +#> 270 B1 52.525253 8.698865886 +#> 271 B1 53.535354 8.601050726 +#> 272 B1 54.545455 8.501919425 +#> 273 B1 55.555556 8.401650008 +#> 274 B1 56.565657 8.300409672 +#> 275 B1 57.575758 8.198355355 +#> 276 B1 58.585859 8.095634277 +#> 277 B1 59.595960 7.992384454 +#> 278 B1 60.606061 7.888735183 +#> 279 B1 61.616162 7.784807509 +#> 280 B1 62.000000 7.745265792 +#> 281 B1 62.626263 7.680714664 +#> 282 B1 63.636364 7.576562482 +#> 283 B1 64.646465 7.472449799 +#> 284 B1 65.656566 7.368468826 +#> 285 B1 66.666667 7.264705509 +#> 286 B1 67.676768 7.161239868 +#> 287 B1 68.686869 7.058146319 +#> 288 B1 69.696970 6.955493978 +#> 289 B1 70.707071 6.853346953 +#> 290 B1 71.717172 6.751764620 +#> 291 B1 72.727273 6.650801882 +#> 292 B1 73.737374 6.550509419 +#> 293 B1 74.747475 6.450933922 +#> 294 B1 75.757576 6.352118318 +#> 295 B1 76.767677 6.254101979 +#> 296 B1 77.777778 6.156920928 +#> 297 B1 78.787879 6.060608023 +#> 298 B1 79.797980 5.965193142 +#> 299 B1 80.808081 5.870703355 +#> 300 B1 81.818182 5.777163083 +#> 301 B1 82.828283 5.684594257 +#> 302 B1 83.838384 5.593016458 +#> 303 B1 84.848485 5.502447062 +#> 304 B1 85.858586 5.412901366 +#> 305 B1 86.868687 5.324392718 +#> 306 B1 87.878788 5.236932630 +#> 307 B1 88.888889 5.150530889 +#> 308 B1 89.898990 5.065195670 +#> 309 B1 90.909091 4.980933628 +#> 310 B1 91.919192 4.897749999 +#> 311 B1 92.929293 4.815648688 +#> 312 B1 93.939394 4.734632351 +#> 313 B1 94.949495 4.654702481 +#> 314 B1 95.959596 4.575859481 +#> 315 B1 96.969697 4.498102737 +#> 316 B1 97.979798 4.421430686 +#> 317 B1 98.989899 4.345840882 +#> 318 B1 100.000000 4.271330056 +#> 319 C1 0.000000 0.000000000 +#> 320 C1 1.000000 1.829645786 +#> 321 C1 1.010101 1.847087763 +#> 322 C1 2.020202 3.492133303 +#> 323 C1 3.000000 4.910531064 +#> 324 C1 3.030303 4.951772742 +#> 325 C1 4.040404 6.241420142 +#> 326 C1 5.050505 7.375351980 +#> 327 C1 6.060606 8.366785999 +#> 328 C1 7.000000 9.171671206 +#> 329 C1 7.070707 9.227954769 +#> 330 C1 8.080808 9.970174354 +#> 331 C1 9.090909 10.603908370 +#> 332 C1 10.101010 11.138827767 +#> 333 C1 11.111111 11.583866567 +#> 334 C1 12.121212 11.947273869 +#> 335 C1 13.131313 12.236662337 +#> 336 C1 14.000000 12.431704739 +#> 337 C1 14.141414 12.459053419 +#> 338 C1 15.151515 12.620919488 +#> 339 C1 16.161616 12.728223141 +#> 340 C1 17.171717 12.786453805 +#> 341 C1 18.181818 12.800661859 +#> 342 C1 19.191919 12.775490422 +#> 343 C1 20.202020 12.715204956 +#> 344 C1 21.212121 12.623720845 +#> 345 C1 22.222222 12.504629065 +#> 346 C1 23.232323 12.361220091 +#> 347 C1 24.242424 12.196506142 +#> 348 C1 25.252525 12.013241882 +#> 349 C1 26.262626 11.813943686 +#> 350 C1 27.272727 11.600907551 +#> 351 C1 28.282828 11.376225763 +#> 352 C1 29.292929 11.141802382 +#> 353 C1 30.000000 10.972842888 +#> 354 C1 30.303030 10.899367648 +#> 355 C1 31.313131 10.650491354 +#> 356 C1 32.323232 10.396595286 +#> 357 C1 33.333333 10.138964763 +#> 358 C1 34.343434 9.878759358 +#> 359 C1 35.353535 9.617022857 +#> 360 C1 36.363636 9.354692485 +#> 361 C1 37.373737 9.092607481 +#> 362 C1 38.383838 8.831517041 +#> 363 C1 39.393939 8.572087685 +#> 364 C1 40.404040 8.314910084 +#> 365 C1 41.414141 8.060505385 +#> 366 C1 42.424242 7.809331068 +#> 367 C1 43.434343 7.561786371 +#> 368 C1 44.444444 7.318217302 +#> 369 C1 45.454545 7.078921287 +#> 370 C1 46.464646 6.844151456 +#> 371 C1 47.474747 6.614120611 +#> 372 C1 48.484848 6.389004885 +#> 373 C1 49.494949 6.168947129 +#> 374 C1 50.505051 5.954060026 +#> 375 C1 51.515152 5.744428970 +#> 376 C1 52.525253 5.540114721 +#> 377 C1 53.535354 5.341155842 +#> 378 C1 54.545455 5.147570951 +#> 379 C1 55.555556 4.959360784 +#> 380 C1 56.565657 4.776510102 +#> 381 C1 57.575758 4.598989433 +#> 382 C1 58.585859 4.426756673 +#> 383 C1 59.595960 4.259758556 +#> 384 C1 60.606061 4.097932000 +#> 385 C1 61.616162 3.941205338 +#> 386 C1 62.000000 3.882970158 +#> 387 C1 62.626263 3.789499444 +#> 388 C1 63.636364 3.642728760 +#> 389 C1 64.646465 3.500802233 +#> 390 C1 65.656566 3.363624171 +#> 391 C1 66.666667 3.231095021 +#> 392 C1 67.676768 3.103112069 +#> 393 C1 68.686869 2.979570086 +#> 394 C1 69.696970 2.860361903 +#> 395 C1 70.707071 2.745378939 +#> 396 C1 71.717172 2.634511667 +#> 397 C1 72.727273 2.527650041 +#> 398 C1 73.737374 2.424683880 +#> 399 C1 74.747475 2.325503203 +#> 400 C1 75.757576 2.229998536 +#> 401 C1 76.767677 2.138061182 +#> 402 C1 77.777778 2.049583458 +#> 403 C1 78.787879 1.964458908 +#> 404 C1 79.797980 1.882582485 +#> 405 C1 80.808081 1.803850715 +#> 406 C1 81.818182 1.728161832 +#> 407 C1 82.828283 1.655415900 +#> 408 C1 83.838384 1.585514911 +#> 409 C1 84.848485 1.518362874 +#> 410 C1 85.858586 1.453865880 +#> 411 C1 86.868687 1.391932162 +#> 412 C1 87.878788 1.332472134 +#> 413 C1 88.888889 1.275398429 +#> 414 C1 89.898990 1.220625918 +#> 415 C1 90.909091 1.168071723 +#> 416 C1 91.919192 1.117655227 +#> 417 C1 92.929293 1.069298066 +#> 418 C1 93.939394 1.022924125 +#> 419 C1 94.949495 0.978459525 +#> 420 C1 95.959596 0.935832597 +#> 421 C1 96.969697 0.894973866 +#> 422 C1 97.979798 0.855816021 +#> 423 C1 98.989899 0.818293881 +#> 424 C1 100.000000 0.782344364 +#> 425 A2 0.000000 0.000000000 +#> 426 A2 1.000000 0.005272357 +#> 427 A2 1.010101 0.005377817 +#> 428 A2 2.020202 0.020885524 +#> 429 A2 3.000000 0.044759575 +#> 430 A2 3.030303 0.045628064 +#> 431 A2 4.040404 0.078765936 +#> 432 A2 5.050505 0.119512155 +#> 433 A2 6.060606 0.167129381 +#> 434 A2 7.000000 0.216973934 +#> 435 A2 7.070707 0.220927189 +#> 436 A2 8.080808 0.280259484 +#> 437 A2 9.090909 0.344522046 +#> 438 A2 10.101010 0.413150206 +#> 439 A2 11.111111 0.485616641 +#> 440 A2 12.121212 0.561429288 +#> 441 A2 13.131313 0.640129357 +#> 442 A2 14.000000 0.709794102 +#> 443 A2 14.141414 0.721289460 +#> 444 A2 15.151515 0.804511827 +#> 445 A2 16.161616 0.889426625 +#> 446 A2 17.171717 0.975690359 +#> 447 A2 18.181818 1.062984358 +#> 448 A2 19.191919 1.151013342 +#> 449 A2 20.202020 1.239504068 +#> 450 A2 21.212121 1.328204041 +#> 451 A2 22.222222 1.416880297 +#> 452 A2 23.232323 1.505318253 +#> 453 A2 24.242424 1.593320615 +#> 454 A2 25.252525 1.680706344 +#> 455 A2 26.262626 1.767309680 +#> 456 A2 27.272727 1.852979219 +#> 457 A2 28.282828 1.937577034 +#> 458 A2 29.292929 2.020977853 +#> 459 A2 30.000000 2.078585030 +#> 460 A2 30.303030 2.103068270 +#> 461 A2 31.313131 2.183746011 +#> 462 A2 32.323232 2.262919231 +#> 463 A2 33.333333 2.340505852 +#> 464 A2 34.343434 2.416432940 +#> 465 A2 35.353535 2.490636111 +#> 466 A2 36.363636 2.563058979 +#> 467 A2 37.373737 2.633652622 +#> 468 A2 38.383838 2.702375089 +#> 469 A2 39.393939 2.769190926 +#> 470 A2 40.404040 2.834070737 +#> 471 A2 41.414141 2.896990764 +#> 472 A2 42.424242 2.957932489 +#> 473 A2 43.434343 3.016882265 +#> 474 A2 44.444444 3.073830964 +#> 475 A2 45.454545 3.128773647 +#> 476 A2 46.464646 3.181709250 +#> 477 A2 47.474747 3.232640290 +#> 478 A2 48.484848 3.281572591 +#> 479 A2 49.494949 3.328515022 +#> 480 A2 50.505051 3.373479253 +#> 481 A2 51.515152 3.416479521 +#> 482 A2 52.525253 3.457532417 +#> 483 A2 53.535354 3.496656681 +#> 484 A2 54.545455 3.533873012 +#> 485 A2 55.555556 3.569203883 +#> 486 A2 56.565657 3.602673379 +#> 487 A2 57.575758 3.634307034 +#> 488 A2 58.585859 3.664131686 +#> 489 A2 59.595960 3.692175334 +#> 490 A2 60.606061 3.718467012 +#> 491 A2 61.616162 3.743036663 +#> 492 A2 62.000000 3.751927986 +#> 493 A2 62.626263 3.765915028 +#> 494 A2 63.636364 3.787133539 +#> 495 A2 64.646465 3.806724217 +#> 496 A2 65.656566 3.824719582 +#> 497 A2 66.666667 3.841152565 +#> 498 A2 67.676768 3.856056426 +#> 499 A2 68.686869 3.869464684 +#> 500 A2 69.696970 3.881411040 +#> 501 A2 70.707071 3.891929316 +#> 502 A2 71.717172 3.901053396 +#> 503 A2 72.727273 3.908817168 +#> 504 A2 73.737374 3.915254472 +#> 505 A2 74.747475 3.920399054 +#> 506 A2 75.757576 3.924284521 +#> 507 A2 76.767677 3.926944303 +#> 508 A2 77.777778 3.928411610 +#> 509 A2 78.787879 3.928719404 +#> 510 A2 79.797980 3.927900364 +#> 511 A2 80.808081 3.925986861 +#> 512 A2 81.818182 3.923010926 +#> 513 A2 82.828283 3.919004234 +#> 514 A2 83.838384 3.913998077 +#> 515 A2 84.848485 3.908023347 +#> 516 A2 85.858586 3.901110518 +#> 517 A2 86.868687 3.893289633 +#> 518 A2 87.878788 3.884590288 +#> 519 A2 88.888889 3.875041619 +#> 520 A2 89.898990 3.864672297 +#> 521 A2 90.909091 3.853510511 +#> 522 A2 91.919192 3.841583970 +#> 523 A2 92.929293 3.828919886 +#> 524 A2 93.939394 3.815544978 +#> 525 A2 94.949495 3.801485462 +#> 526 A2 95.959596 3.786767051 +#> 527 A2 96.969697 3.771414951 +#> 528 A2 97.979798 3.755453860 +#> 529 A2 98.989899 3.738907968 +#> 530 A2 100.000000 3.721800959 +#> +#> $cost +#> function (P) +#> { +#> assign("calls", calls + 1, inherits = TRUE) +#> if (trace_parms) +#> cat(P, "\n") +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> transparms.fixed) +#> parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, +#> transform_fractions = transform_fractions) +#> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> if (mC$model < cost.old) { +#> if (!quiet) +#> cat("Model cost at call ", calls, ": ", mC$model, +#> "\n") +#> if (plot) { +#> outtimes_plot = seq(min(observed$time), max(observed$time), +#> length.out = 100) +#> out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, +#> solution_type = solution_type, use_compiled = use_compiled, +#> method.ode = method.ode, atol = atol, rtol = rtol, +#> ...) +#> plot(0, type = "n", xlim = range(observed$time), +#> ylim = c(0, max(observed$value, na.rm = TRUE)), +#> xlab = "Time", ylab = "Observed") +#> col_obs <- pch_obs <- 1:length(obs_vars) +#> lty_obs <- rep(1, length(obs_vars)) +#> names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars +#> for (obs_var in obs_vars) { +#> points(subset(observed, name == obs_var, c(time, +#> value)), pch = pch_obs[obs_var], col = col_obs[obs_var]) +#> } +#> matlines(out_plot$time, out_plot[-1], col = col_obs, +#> lty = lty_obs) +#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, +#> col = col_obs, pch = pch_obs, lty = 1:length(pch_obs)) +#> } +#> assign("cost.old", mC$model, inherits = TRUE) +#> } +#> return(mC) +#> } +#> <environment: 0x36a83b0> +#> +#> $cost_notrans +#> function (P) +#> { +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> parms.fixed) +#> out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> return(mC) +#> } +#> <environment: 0x36a83b0> +#> +#> $hessian_notrans +#> parent_0 k_parent k_A1 k_B1 +#> parent_0 7.365081 -1854.5113 -7.186039e+02 -1.307858e+02 +#> k_parent -1854.511330 2686790.7676 -6.235542e+04 -1.429363e+04 +#> k_A1 -718.603865 -62355.4211 3.128242e+06 0.000000e+00 +#> k_B1 -130.785796 -14293.6348 0.000000e+00 4.545506e+05 +#> k_C1 -76.404274 -38575.9391 1.190516e-02 -9.422820e-04 +#> k_A2 -17.933942 -4390.5079 -5.838973e+04 0.000000e+00 +#> f_parent_to_A1 75.150866 43257.2599 -1.733841e+05 0.000000e+00 +#> f_parent_to_B1 29.265575 17940.1132 0.000000e+00 -6.150198e+04 +#> f_parent_to_C1 20.661354 19692.5582 -6.146186e-05 -1.990817e-03 +#> f_A1_to_A2 1.593279 597.0744 5.849840e+03 0.000000e+00 +#> k_C1 k_A2 f_parent_to_A1 f_parent_to_B1 +#> parent_0 -7.640427e+01 -1.793394e+01 7.515087e+01 2.926558e+01 +#> k_parent -3.857594e+04 -4.390508e+03 4.325726e+04 1.794011e+04 +#> k_A1 1.190516e-02 -5.838973e+04 -1.733841e+05 0.000000e+00 +#> k_B1 -9.422820e-04 0.000000e+00 0.000000e+00 -6.150198e+04 +#> k_C1 8.855106e+04 4.105787e-04 -1.354551e-03 5.852620e-04 +#> k_A2 4.105787e-04 4.649850e+04 -4.327086e+03 0.000000e+00 +#> f_parent_to_A1 -1.354551e-03 -4.327086e+03 1.813234e+04 0.000000e+00 +#> f_parent_to_B1 5.852620e-04 0.000000e+00 0.000000e+00 1.376213e+04 +#> f_parent_to_C1 -1.658031e+04 2.903794e-04 1.946385e-03 1.325258e-03 +#> f_A1_to_A2 -4.367402e-05 -3.679910e+03 3.844249e+02 0.000000e+00 +#> f_parent_to_C1 f_A1_to_A2 +#> parent_0 2.066135e+01 1.593279e+00 +#> k_parent 1.969256e+04 5.970744e+02 +#> k_A1 -6.146186e-05 5.849840e+03 +#> k_B1 -1.990817e-03 0.000000e+00 +#> k_C1 -1.658031e+04 -4.367402e-05 +#> k_A2 2.903794e-04 -3.679910e+03 +#> f_parent_to_A1 1.946385e-03 3.844249e+02 +#> f_parent_to_B1 1.325258e-03 0.000000e+00 +#> f_parent_to_C1 4.483759e+03 -3.796730e-05 +#> f_A1_to_A2 -3.796730e-05 3.269288e+02 +#> +#> $start +#> value type +#> parent_0 93.2000000 state +#> k_parent 0.1000000 deparm +#> k_A1 0.1001000 deparm +#> k_B1 0.1002000 deparm +#> k_C1 0.1003000 deparm +#> k_A2 0.1004000 deparm +#> f_parent_to_A1 0.3333333 deparm +#> f_parent_to_B1 0.3333333 deparm +#> f_parent_to_C1 0.3333333 deparm +#> f_A1_to_A2 0.5000000 deparm +#> +#> $start_transformed +#> value lower upper +#> parent_0 93.200000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_A1 -2.301586 -Inf Inf +#> log_k_B1 -2.300587 -Inf Inf +#> log_k_C1 -2.299590 -Inf Inf +#> log_k_A2 -2.298593 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> f_parent_ilr_2 0.000000 -Inf Inf +#> f_A1_ilr_1 0.000000 -Inf Inf +#> +#> $fixed +#> value type +#> A1_0 0 state +#> B1_0 0 state +#> C1_0 0 state +#> A2_0 0 state +#> +#> $data +#> time variable observed predicted residual +#> 1 0 parent 93.20 91.918159794 1.2818402 +#> 2 1 parent 89.40 87.462788491 1.9372115 +#> 3 3 parent 79.70 79.189448055 0.5105519 +#> 4 7 parent 61.10 64.916531757 -3.8165318 +#> 5 14 parent 48.20 45.846828365 2.3531716 +#> 6 30 parent 15.90 20.704334210 -4.8043342 +#> 7 62 parent 6.50 4.222456793 2.2775432 +#> 8 100 parent 6.00 0.639147580 5.3608524 +#> 9 0 A1 NA 0.000000000 NA +#> 10 1 A1 NA 1.685461006 NA +#> 11 3 A1 0.55 4.746752202 -4.1967522 +#> 12 7 A1 6.87 9.773298725 -2.9032987 +#> 13 14 A1 17.08 15.767512526 1.3124875 +#> 14 30 A1 21.68 21.077890710 0.6021093 +#> 15 62 A1 15.77 18.279232408 -2.5092324 +#> 16 100 A1 13.63 11.743860400 1.8861396 +#> 17 0 B1 NA 0.000000000 NA +#> 18 1 B1 NA 0.862762059 NA +#> 19 3 B1 NA 2.418226457 NA +#> 20 7 B1 0.55 4.930176837 -4.3801768 +#> 21 14 B1 2.31 7.810248132 -5.5002481 +#> 22 30 B1 15.76 9.968281596 5.7917184 +#> 23 62 B1 6.36 7.745265792 -1.3852658 +#> 24 100 B1 3.74 4.271330056 -0.5313301 +#> 25 0 C1 NA 0.000000000 NA +#> 26 1 C1 0.55 1.829645786 -1.2796458 +#> 27 3 C1 3.20 4.910531064 -1.7105311 +#> 28 7 C1 5.46 9.171671206 -3.7116712 +#> 29 14 C1 12.55 12.431704739 0.1182953 +#> 30 30 C1 10.45 10.972842888 -0.5228429 +#> 31 62 C1 4.74 3.882970158 0.8570298 +#> 32 100 C1 4.33 0.782344364 3.5476556 +#> 33 0 A2 NA 0.000000000 NA +#> 34 1 A2 0.55 0.005272357 0.5447276 +#> 35 3 A2 1.41 0.044759575 1.3652404 +#> 36 7 A2 0.55 0.216973934 0.3330261 +#> 37 14 A2 1.29 0.709794102 0.5802059 +#> 38 30 A2 1.95 2.078585030 -0.1285850 +#> 39 62 A2 3.54 3.751927986 -0.2119280 +#> 40 100 A2 3.86 3.721800959 0.1381990 +#> +#> $atol +#> [1] 1e-08 +#> +#> $rtol +#> [1] 1e-10 +#> +#> $weight.ini +#> [1] "none" +#> +#> $reweight.tol +#> [1] 1e-08 +#> +#> $reweight.max.iter +#> [1] 10 +#> +#> $bparms.optim +#> parent_0 k_parent k_A1 k_B1 k_C1 +#> 91.91815979 0.04968519 0.01393165 0.01859846 0.06171564 +#> k_A2 f_parent_to_A1 f_parent_to_B1 f_parent_to_C1 f_A1_to_A2 +#> 0.02431549 0.38096192 0.19546676 0.42357132 0.44796066 +#> +#> $bparms.fixed +#> A1_0 B1_0 C1_0 A2_0 +#> 0 0 0 0 +#> +#> $bparms.ode +#> k_parent f_parent_to_A1 f_parent_to_B1 f_parent_to_C1 k_A1 +#> 0.04968519 0.38096192 0.19546676 0.42357132 0.01393165 +#> f_A1_to_A2 k_B1 k_C1 k_A2 +#> 0.44796066 0.01859846 0.06171564 0.02431549 +#> +#> $bparms.state +#> parent A1 B1 C1 A2 +#> 91.91816 0.00000 0.00000 0.00000 0.00000 +#> +#> $date +#> [1] "Fri Nov 18 15:20:45 2016" +#> +#> attr(,"class") +#> [1] "mkinfit" "modFit"
#> Successfully compiled differential equation model from auto-generated C code.
+fit.ff <- 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(fit.ff, data = FALSE)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:20:52 2016 +#> Date of summary: Fri Nov 18 15:20:52 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 0.764 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
initials <- c("f_parent_to_m1" = 0.5) +transformed <- transform_odeparms(initials, SFO_SFO.ff) +backtransform_odeparms(transformed, SFO_SFO.ff)
#> f_parent_to_m1 +#> 0.5
+# And without sink +SFO_SFO.ff.2 <- mkinmod( + parent = list(type = "SFO", to = "m1", sink = FALSE), + m1 = list(type = "SFO"), + use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
+ +fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D)
#> Model cost at call 1 : 12435.14 +#> Model cost at call 2 : 12435.14 +#> Model cost at call 5 : 8276.306 +#> Model cost at call 6 : 8276.294 +#> Model cost at call 7 : 8275.676 +#> Model cost at call 9 : 5256.953 +#> Model cost at call 11 : 5256.951 +#> Model cost at call 12 : 5256.943 +#> Model cost at call 14 : 4469.745 +#> Model cost at call 18 : 4462.927 +#> Model cost at call 21 : 4462.925 +#> Model cost at call 22 : 4376.059 +#> Model cost at call 24 : 4376.058 +#> Model cost at call 27 : 4366.956 +#> Model cost at call 29 : 4366.956 +#> Model cost at call 31 : 4365.275 +#> Model cost at call 33 : 4365.275 +#> Model cost at call 35 : 4351.877 +#> Model cost at call 37 : 4351.877 +#> Model cost at call 39 : 4338.109 +#> Model cost at call 41 : 4338.109 +#> Model cost at call 43 : 4297.053 +#> Model cost at call 44 : 4218.591 +#> Model cost at call 45 : 3940.397 +#> Model cost at call 46 : 3690.395 +#> Model cost at call 48 : 3690.395 +#> Model cost at call 49 : 3690.385 +#> Model cost at call 50 : 3038.366 +#> Model cost at call 53 : 3038.365 +#> Model cost at call 54 : 2637.866 +#> Model cost at call 57 : 2637.865 +#> Model cost at call 59 : 2588.01 +#> Model cost at call 60 : 2588.009 +#> Model cost at call 63 : 2576.742 +#> Model cost at call 66 : 2576.742 +#> Model cost at call 67 : 2574 +#> Model cost at call 68 : 2574 +#> Model cost at call 69 : 2574 +#> Model cost at call 71 : 2569.76 +#> Model cost at call 73 : 2569.76 +#> Model cost at call 74 : 2569.76 +#> Model cost at call 75 : 2569.403 +#> Model cost at call 76 : 2569.403 +#> Model cost at call 79 : 2569.4 +#> Model cost at call 80 : 2569.4 +#> Model cost at call 81 : 2569.4 +#> Model cost at call 83 : 2569.4 +#> Model cost at call 86 : 2569.4 +#> Model cost at call 90 : 2569.4 +#> Model cost at call 99 : 2569.4 +#> Model cost at call 100 : 2569.4 +#> Optimisation by method Port successfully terminated.
summary(fit.ff.2, data = FALSE)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:20:52 2016 +#> Date of summary: Fri Nov 18 15:20:52 2016 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 104 model solutions performed in 0.44 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 +#> +#> 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 +#> +#> Fixed parameter values: +#> value type +#> m1_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 84.790 2.96500 78.78 90.800 +#> log_k_parent -2.756 0.08088 -2.92 -2.593 +#> log_k_m1 -4.214 0.11150 -4.44 -3.988 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 +#> parent_0 1.0000 0.11059 0.46156 +#> log_k_parent 0.1106 1.00000 0.06274 +#> log_k_m1 0.4616 0.06274 1.00000 +#> +#> Residual standard error: 8.333 on 37 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 84.79000 28.600 3.939e-27 78.78000 90.80000 +#> k_parent 0.06352 12.360 5.237e-15 0.05392 0.07483 +#> k_m1 0.01478 8.966 4.114e-11 0.01179 0.01853 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 19.66 3 16 +#> parent 17.56 2 7 +#> m1 18.71 1 9 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 10.91 36.25 +#> m1 46.89 155.75
+