From f09b8d80435a884b10965b95868260037ee1c39a Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 5 Jan 2018 13:39:19 +0100 Subject: Experimental test data from UBA 2014 expertise - Typo in synthetic data for UBA - Static documentation except articles rebuilt by pkgdown --- docs/reference/index.html | 2 +- docs/reference/synthetic_data_for_UBA.html | 2 +- docs/reference/test_data_from_UBA_2014-16.png | Bin 0 -> 14867 bytes docs/reference/test_data_from_UBA_2014-6.png | Bin 0 -> 11121 bytes docs/reference/test_data_from_UBA_2014.html | 411 ++++++++++++++++++++++++++ 5 files changed, 413 insertions(+), 2 deletions(-) create mode 100644 docs/reference/test_data_from_UBA_2014-16.png create mode 100644 docs/reference/test_data_from_UBA_2014-6.png create mode 100644 docs/reference/test_data_from_UBA_2014.html (limited to 'docs') diff --git a/docs/reference/index.html b/docs/reference/index.html index dbcd5ba0..e047f75d 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -100,7 +100,7 @@ diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html index 9ff18876..8a148870 100644 --- a/docs/reference/synthetic_data_for_UBA.html +++ b/docs/reference/synthetic_data_for_UBA.html @@ -122,7 +122,7 @@

Format

A list containing datasets in the form internally used by the 'gmkin' package. - The list has twelfe components. Each of the components is one dataset that has, + The list has twelve components. Each of the components is one dataset that has, among others, the following components

title

The name of the dataset, e.g. SFO_lin_a

data

A data frame with the data in the form expected by mkinfit

diff --git a/docs/reference/test_data_from_UBA_2014-16.png b/docs/reference/test_data_from_UBA_2014-16.png new file mode 100644 index 00000000..e5346b43 Binary files /dev/null and b/docs/reference/test_data_from_UBA_2014-16.png differ diff --git a/docs/reference/test_data_from_UBA_2014-6.png b/docs/reference/test_data_from_UBA_2014-6.png new file mode 100644 index 00000000..e7fe4f0c Binary files /dev/null and b/docs/reference/test_data_from_UBA_2014-6.png differ diff --git a/docs/reference/test_data_from_UBA_2014.html b/docs/reference/test_data_from_UBA_2014.html new file mode 100644 index 00000000..601f148c --- /dev/null +++ b/docs/reference/test_data_from_UBA_2014.html @@ -0,0 +1,411 @@ + + + + + + + + +Three experimental datasets from two water sediment systems and one soil — test_data_from_UBA_2014 • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+ + + +

The datasets were used for the comparative validation of several kinetic evaluation + software packages (Ranke, 2014).

+ + +
test_data_from_UBA_2014
+ +

Format

+ +

A list containing three datasets as an R6 class defined by mkinds. + Each dataset has, among others, the following components

+
title

The name of the dataset, e.g. UBA_2014_WS_river

+
data

A data frame with the data in the form expected by mkinfit

+
+ +

Source

+ +

Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative + zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452

+ + +

Examples

+
# This is a level P-II evaluation of the dataset according to the FOCUS kinetics + # guidance. Due to the strong correlation of the parameter estimates, the + # covariance matrix is not returned. Note that level P-II evaluations are + # generally considered deprecated due to the frequent occurrence of such + # large parameter correlations, among other reasons (e.g. the adequacy of the + # model). + m_ws <- mkinmod(parent_w = mkinsub("SFO", "parent_s"), + parent_s = mkinsub("SFO", "parent_w"))
#> Successfully compiled differential equation model from auto-generated C code.
f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data)
#> Model cost at call 1 : 2371.755 +#> Model cost at call 3 : 2371.755 +#> Model cost at call 7 : 457.5705 +#> Model cost at call 10 : 457.5608 +#> Model cost at call 14 : 297.2882 +#> Model cost at call 16 : 297.2882 +#> Model cost at call 18 : 297.2881 +#> Model cost at call 21 : 275.6034 +#> Model cost at call 23 : 275.6034 +#> Model cost at call 27 : 268.2102 +#> Model cost at call 29 : 268.2101 +#> Model cost at call 33 : 255.941 +#> Model cost at call 35 : 255.941 +#> Model cost at call 39 : 246.486 +#> Model cost at call 41 : 246.486 +#> Model cost at call 45 : 231.4275 +#> Model cost at call 47 : 231.4275 +#> Model cost at call 51 : 212.4338 +#> Model cost at call 52 : 212.4338 +#> Model cost at call 53 : 212.4337 +#> Model cost at call 57 : 203.7185 +#> Model cost at call 58 : 203.7185 +#> Model cost at call 63 : 198.3304 +#> Model cost at call 69 : 198.3304 +#> Model cost at call 70 : 195.794 +#> Model cost at call 72 : 195.7939 +#> Model cost at call 76 : 195.2477 +#> Model cost at call 77 : 195.2477 +#> Model cost at call 82 : 191.6184 +#> Model cost at call 84 : 191.6184 +#> Model cost at call 88 : 189.9011 +#> Model cost at call 90 : 189.9011 +#> Model cost at call 91 : 189.9011 +#> Model cost at call 94 : 189.223 +#> Model cost at call 95 : 189.223 +#> Model cost at call 100 : 188.8728 +#> Model cost at call 101 : 188.8728 +#> Model cost at call 103 : 188.8728 +#> Model cost at call 106 : 188.2057 +#> Model cost at call 107 : 188.2057 +#> Model cost at call 112 : 187.8429 +#> Model cost at call 118 : 187.6219 +#> Model cost at call 119 : 187.3931 +#> Model cost at call 121 : 187.3931 +#> Model cost at call 125 : 187.1236 +#> Model cost at call 126 : 187.1236 +#> Model cost at call 131 : 186.9995 +#> Model cost at call 137 : 186.927 +#> Model cost at call 139 : 186.927 +#> Model cost at call 143 : 186.8909 +#> Model cost at call 146 : 186.8909 +#> Model cost at call 150 : 186.8708 +#> Model cost at call 152 : 186.8708 +#> Model cost at call 157 : 186.8606 +#> Model cost at call 159 : 186.8606 +#> Model cost at call 161 : 186.8606 +#> Model cost at call 162 : 186.8606 +#> Model cost at call 167 : 186.8551 +#> Model cost at call 169 : 186.8551 +#> Model cost at call 176 : 186.8519 +#> Model cost at call 177 : 186.8519 +#> Model cost at call 180 : 186.8519 +#> Model cost at call 181 : 186.8519 +#> Model cost at call 186 : 186.8504 +#> Model cost at call 187 : 186.8504 +#> Model cost at call 196 : 186.8496 +#> Model cost at call 197 : 186.8496 +#> Model cost at call 200 : 186.8496 +#> Model cost at call 206 : 186.8493 +#> Model cost at call 211 : 186.8493 +#> Model cost at call 215 : 186.8493 +#> Model cost at call 216 : 186.8491 +#> Model cost at call 225 : 186.8491 +#> Model cost at call 226 : 186.849 +#> Model cost at call 236 : 186.8489 +#> Model cost at call 246 : 186.8489 +#> Model cost at call 254 : 186.8489 +#> Model cost at call 257 : 186.8489 +#> Model cost at call 265 : 186.8489 +#> Model cost at call 268 : 186.8489 +#> Model cost at call 276 : 186.8489 +#> Model cost at call 279 : 186.8489 +#> Model cost at call 287 : 186.8489 +#> Model cost at call 290 : 186.8489 +#> Model cost at call 298 : 186.8489 +#> Model cost at call 301 : 186.8489 +#> Model cost at call 309 : 186.8489 +#> Model cost at call 312 : 186.8489 +#> Model cost at call 320 : 186.8489 +#> Model cost at call 323 : 186.8489 +#> Model cost at call 331 : 186.8489 +#> Model cost at call 334 : 186.8489 +#> Model cost at call 342 : 186.8489 +#> Model cost at call 345 : 186.8489 +#> Model cost at call 353 : 186.8489 +#> Model cost at call 356 : 186.8489 +#> Model cost at call 367 : 186.8489 +#> Model cost at call 374 : 186.8489 +#> Model cost at call 375 : 186.8489 +#> Model cost at call 380 : 186.8489 +#> Model cost at call 382 : 186.8489 +#> Model cost at call 383 : 186.8489 +#> Optimisation by method Port successfully terminated.
plot(f_river)
+ summary(f_river)$bpar
#> Estimate se_notrans t value Pr(>t) Lower +#> parent_w_0 9.598567e+01 2.33959810 4.102657e+01 9.568973e-19 NA +#> k_parent_w_sink 3.603743e-01 0.03497716 1.030313e+01 4.988281e-09 NA +#> k_parent_w_parent_s 6.031370e-02 0.01746026 3.454342e+00 1.514738e-03 NA +#> k_parent_s_sink 5.099834e-11 0.10381939 4.912217e-10 5.000000e-01 NA +#> k_parent_s_parent_w 7.419672e-02 0.11338174 6.543974e-01 2.608057e-01 NA +#> Upper +#> parent_w_0 NA +#> k_parent_w_sink NA +#> k_parent_w_parent_s NA +#> k_parent_s_sink NA +#> k_parent_s_parent_w NA
mkinerrmin(f_river)
#> err.min n.optim df +#> All data 0.09246946 5 6 +#> parent_w 0.06377096 3 3 +#> parent_s 0.20882324 2 3
+ # This is the evaluation used for the validation of software packages + # in the expertise from 2014 + m_soil <- mkinmod(parent = mkinsub("SFO", c("M1", "M2")), + M1 = mkinsub("SFO", "M3"), + M2 = mkinsub("SFO", "M3"), + M3 = mkinsub("SFO"), + use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
+ f_soil <- mkinfit(m_soil, test_data_from_UBA_2014[[3]]$data)
#> Model cost at call 1 : 340.115 +#> Model cost at call 3 : 340.115 +#> Model cost at call 12 : 278.5521 +#> Model cost at call 14 : 278.5499 +#> Model cost at call 22 : 244.4153 +#> Model cost at call 24 : 244.4152 +#> Model cost at call 32 : 211.0249 +#> Model cost at call 34 : 211.0247 +#> Model cost at call 42 : 151.2576 +#> Model cost at call 44 : 151.2575 +#> Model cost at call 46 : 151.2574 +#> Model cost at call 52 : 109.7633 +#> Model cost at call 53 : 100.8415 +#> Model cost at call 58 : 100.8412 +#> Model cost at call 61 : 100.8412 +#> Model cost at call 62 : 100.8411 +#> Model cost at call 64 : 70.07576 +#> Model cost at call 66 : 70.07568 +#> Model cost at call 76 : 64.29488 +#> Model cost at call 78 : 64.29487 +#> Model cost at call 86 : 61.39756 +#> Model cost at call 88 : 61.39755 +#> Model cost at call 96 : 57.47933 +#> Model cost at call 98 : 57.47932 +#> Model cost at call 106 : 52.46647 +#> Model cost at call 108 : 52.46646 +#> Model cost at call 116 : 48.17301 +#> Model cost at call 118 : 48.173 +#> Model cost at call 126 : 45.15666 +#> Model cost at call 128 : 45.15665 +#> Model cost at call 137 : 44.55574 +#> Model cost at call 139 : 44.55573 +#> Model cost at call 143 : 44.55573 +#> Model cost at call 147 : 43.13847 +#> Model cost at call 149 : 43.13847 +#> Model cost at call 151 : 43.13847 +#> Model cost at call 158 : 43.11922 +#> Model cost at call 160 : 43.11922 +#> Model cost at call 168 : 42.29535 +#> Model cost at call 170 : 42.29535 +#> Model cost at call 178 : 42.03979 +#> Model cost at call 180 : 42.03979 +#> Model cost at call 189 : 41.56286 +#> Model cost at call 190 : 41.12187 +#> Model cost at call 191 : 39.73019 +#> Model cost at call 192 : 39.31762 +#> Model cost at call 193 : 39.31762 +#> Model cost at call 196 : 39.31762 +#> Model cost at call 203 : 38.6346 +#> Model cost at call 204 : 38.6346 +#> Model cost at call 205 : 38.63459 +#> Model cost at call 209 : 38.63459 +#> Model cost at call 210 : 38.63459 +#> Model cost at call 211 : 38.63459 +#> Model cost at call 213 : 38.12767 +#> Model cost at call 215 : 38.12767 +#> Model cost at call 223 : 38.04349 +#> Model cost at call 225 : 38.04349 +#> Model cost at call 229 : 38.04349 +#> Model cost at call 233 : 37.93963 +#> Model cost at call 236 : 37.93963 +#> Model cost at call 243 : 37.87645 +#> Model cost at call 244 : 37.87645 +#> Model cost at call 254 : 37.79144 +#> Model cost at call 256 : 37.79144 +#> Model cost at call 264 : 37.7493 +#> Model cost at call 269 : 37.7493 +#> Model cost at call 274 : 37.72466 +#> Model cost at call 275 : 37.72466 +#> Model cost at call 279 : 37.72466 +#> Model cost at call 283 : 37.72466 +#> Model cost at call 284 : 37.71402 +#> Model cost at call 285 : 37.71402 +#> Model cost at call 287 : 37.71402 +#> Model cost at call 294 : 37.70366 +#> Model cost at call 295 : 37.70366 +#> Model cost at call 296 : 37.70366 +#> Model cost at call 305 : 37.69553 +#> Model cost at call 306 : 37.69553 +#> Model cost at call 307 : 37.69553 +#> Model cost at call 315 : 37.6936 +#> Model cost at call 319 : 37.6936 +#> Model cost at call 321 : 37.6936 +#> Model cost at call 326 : 37.6924 +#> Model cost at call 328 : 37.6924 +#> Model cost at call 329 : 37.6924 +#> Model cost at call 336 : 37.69198 +#> Model cost at call 338 : 37.69198 +#> Model cost at call 344 : 37.69198 +#> Model cost at call 348 : 37.69197 +#> Model cost at call 350 : 37.69197 +#> Model cost at call 363 : 37.69197 +#> Model cost at call 364 : 37.69197 +#> Model cost at call 367 : 37.69197 +#> Model cost at call 382 : 37.69197 +#> Model cost at call 384 : 37.69197 +#> Model cost at call 387 : 37.69197 +#> Model cost at call 401 : 37.69197 +#> Model cost at call 420 : 37.69197 +#> Model cost at call 441 : 37.69197 +#> Optimisation by method Port successfully terminated.
plot(f_soil)
summary(f_soil)$bpar
#> Estimate se_notrans t value Pr(>t) Lower +#> parent_0 76.55425583 0.943443834 81.1434164 4.422340e-30 74.602593306 +#> k_parent 0.12081956 0.004815515 25.0896457 1.639665e-18 0.111257526 +#> k_M1 0.84258650 0.930121206 0.9058889 1.871937e-01 0.085876305 +#> k_M2 0.04210878 0.013729902 3.0669396 2.729137e-03 0.021450631 +#> k_M3 0.01122919 0.008044866 1.3958205 8.804914e-02 0.002550985 +#> f_parent_to_M1 0.32240199 0.278620411 1.1571370 1.295466e-01 NA +#> f_parent_to_M2 0.16099854 0.030548889 5.2701930 1.196191e-05 NA +#> f_M1_to_M3 0.27921500 0.314732717 0.8871496 1.920907e-01 0.015016888 +#> f_M2_to_M3 0.55641332 0.650247079 0.8556952 2.004966e-01 0.005360551 +#> Upper +#> parent_0 78.50591836 +#> k_parent 0.13120340 +#> k_M1 8.26714671 +#> k_M2 0.08266187 +#> k_M3 0.04942980 +#> f_parent_to_M1 NA +#> f_parent_to_M2 NA +#> f_M1_to_M3 0.90777217 +#> f_M2_to_M3 0.99658634
mkinerrmin(f_soil)
#> err.min n.optim df +#> All data 0.09649963 9 20 +#> parent 0.04721283 2 6 +#> M1 0.26551209 2 5 +#> M2 0.20327575 2 5 +#> M3 0.05196549 3 4
+
+ +
+ + +
+ + + -- cgit v1.2.1