Three experimental datasets from two water sediment systems and one soil

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

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test_data_from_UBA_2014

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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

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Examples

  # \dontrun{
-  # 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"))
-#> Temporary DLL for differentials generated and loaded
-  f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-  plot_sep(f_river)
-
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-  summary(f_river)$bpar
-#> Warning: Could not calculate correlation; no covariance matrix
-#>                           Estimate se_notrans t value Pr(>t) Lower Upper
-#> parent_w_0             95.91998118         NA      NA     NA    NA    NA
-#> k_parent_w              0.41145375         NA      NA     NA    NA    NA
-#> k_parent_s              0.04663944         NA      NA     NA    NA    NA
-#> f_parent_w_to_parent_s  0.12467894         NA      NA     NA    NA    NA
-#> f_parent_s_to_parent_w  0.50000000         NA      NA     NA    NA    NA
-#> sigma                   3.13612618         NA      NA     NA    NA    NA
-  mkinerrmin(f_river)
-#>            err.min n.optim df
-#> All data 0.1090929       5  6
-#> parent_w 0.0817436       3  3
-#> parent_s 0.1619965       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")
-#> Temporary DLL for differentials generated and loaded
-
-  f_soil <- mkinfit(m_soil, test_data_from_UBA_2014[[3]]$data, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-  plot_sep(f_soil, lpos = c("topright", "topright", "topright", "bottomright"))
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-  summary(f_soil)$bpar
-#>                   Estimate  se_notrans    t value       Pr(>t)        Lower
-#> parent_0       76.55425650 0.859186399 89.1008710 1.113861e-26 74.755959418
-#> k_parent        0.12081956 0.004601918 26.2541722 1.077359e-16  0.111561575
-#> k_M1            0.84258615 0.806160102  1.0451846 1.545268e-01  0.113779609
-#> k_M2            0.04210880 0.017083034  2.4649483 1.170188e-02  0.018013857
-#> k_M3            0.01122918 0.007245856  1.5497385 6.885052e-02  0.002909431
-#> f_parent_to_M1  0.32240200 0.240783943  1.3389680 9.819076e-02           NA
-#> f_parent_to_M2  0.16099855 0.033691952  4.7785464 6.531136e-05           NA
-#> f_M1_to_M3      0.27921507 0.269423780  1.0363416 1.565267e-01  0.022978205
-#> f_M2_to_M3      0.55641252 0.595119966  0.9349586 1.807707e-01  0.008002509
-#> sigma           1.14005399 0.149696423  7.6157731 1.727024e-07  0.826735778
-#>                      Upper
-#> parent_0       78.35255358
-#> k_parent        0.13084582
-#> k_M1            6.23970702
-#> k_M2            0.09843260
-#> k_M3            0.04333992
-#> f_parent_to_M1          NA
-#> f_parent_to_M2          NA
-#> f_M1_to_M3      0.86450775
-#> f_M2_to_M3      0.99489895
-#> sigma           1.45337221
-  mkinerrmin(f_soil)
-#>             err.min n.optim df
-#> All data 0.09649963       9 20
-#> parent   0.04721283       2  6
-#> M1       0.26551208       2  5
-#> M2       0.20327575       2  5
-#> M3       0.05196550       3  4
-  # }
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