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 @@

Reference - version 0.9.46.3 + version 0.9.47.1

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 + + + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Three experimental datasets from two water sediment systems and one soil

+
+ + +

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