From db9ae6a0c9cecb92048fde6f06af1da183c09b5f Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 19 Nov 2020 15:41:24 +0100 Subject: Depend on parallel, doc improvements By depending on parallel instead of importing it, functions to set up and stop a cluster are always available when mkin is loaded. The use of multicore processing in mmkin on Windows is now documented in the help file, which brings mkin closer to a version 1.0 #9. --- docs/dev/articles/FOCUS_D.html | 113 ++--- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 ++ .../articles/FOCUS_D_files/figure-html/plot-1.png | Bin 101350 -> 81432 bytes .../FOCUS_D_files/figure-html/plot_2-1.png | Bin 15733 -> 24025 bytes docs/dev/articles/FOCUS_L.html | 248 ++++++----- .../anchor-sections-1.0/anchor-sections.css | 4 + .../anchor-sections-1.0/anchor-sections.js | 33 ++ .../figure-html/unnamed-chunk-10-1.png | Bin 29158 -> 43110 bytes .../figure-html/unnamed-chunk-12-1.png | Bin 54890 -> 84605 bytes .../figure-html/unnamed-chunk-13-1.png | Bin 22017 -> 33489 bytes .../figure-html/unnamed-chunk-15-1.png | Bin 38622 -> 59507 bytes .../figure-html/unnamed-chunk-4-1.png | Bin 23429 -> 35964 bytes .../figure-html/unnamed-chunk-5-1.png | Bin 14826 -> 21999 bytes 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docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css create mode 100644 docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js create mode 100644 docs/dev/reference/D24_2014.html create mode 100644 docs/dev/reference/f_time_norm_focus.html create mode 100644 docs/dev/reference/focus_soil_moisture.html create mode 100644 docs/dev/reference/mkindsg.html create mode 100644 docs/dev/reference/saem-6.png (limited to 'docs/dev') diff --git a/docs/dev/articles/FOCUS_D.html b/docs/dev/articles/FOCUS_D.html index 02701431..e526b3a7 100644 --- a/docs/dev/articles/FOCUS_D.html +++ b/docs/dev/articles/FOCUS_D.html @@ -32,7 +32,7 @@ mkin - 0.9.50.3 + 0.9.50.4 @@ -80,7 +80,7 @@
  • - + @@ -95,15 +95,16 @@ -
    + +

    Calculation of time weighted average concentrations with mkin

    Johannes Ranke

    -

    2020-10-08

    +

    2020-11-19

    - Source: vignettes/twa.rmd + Source: vignettes/twa.rmd
    @@ -162,7 +163,7 @@
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css new file mode 100644 index 00000000..07aee5fc --- /dev/null +++ b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.css @@ -0,0 +1,4 @@ +/* Styles for section anchors */ +a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} +a.anchor-section::before {content: '#';} +.hasAnchor:hover a.anchor-section {visibility: visible;} diff --git a/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js new file mode 100644 index 00000000..570f99a0 --- /dev/null +++ b/docs/dev/articles/twa_files/anchor-sections-1.0/anchor-sections.js @@ -0,0 +1,33 @@ +// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020. +document.addEventListener('DOMContentLoaded', function() { + // Do nothing if AnchorJS is used + if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) { + return; + } + + const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6'); + + // Do nothing if sections are already anchored + if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) { + return null; + } + + // Use section id when pandoc runs with --section-divs + const section_id = function(x) { + return ((x.classList.contains('section') || (x.tagName === 'SECTION')) + ? x.id : ''); + }; + + // Add anchors + h.forEach(function(x) { + const id = x.id || section_id(x.parentElement); + if (id === '') { + return null; + } + let anchor = document.createElement('a'); + anchor.href = '#' + id; + anchor.classList = ['anchor-section']; + x.classList.add('hasAnchor'); + x.appendChild(anchor); + }); +}); diff --git a/docs/dev/articles/web_only/FOCUS_Z.html b/docs/dev/articles/web_only/FOCUS_Z.html index 763ca9be..4cfe6c31 100644 --- a/docs/dev/articles/web_only/FOCUS_Z.html +++ b/docs/dev/articles/web_only/FOCUS_Z.html @@ -32,7 +32,7 @@ mkin - 0.9.50.3 + 0.9.50.4
    @@ -80,7 +80,7 @@
  • - + @@ -95,15 +95,16 @@ -
    + +

    Example evaluation of FOCUS dataset Z

    Johannes Ranke

    -

    2020-10-08

    +

    2020-11-19

    - Source: vignettes/web_only/FOCUS_Z.rmd + Source: vignettes/web_only/FOCUS_Z.rmd
    @@ -115,35 +116,40 @@

    The data

    The following code defines the example dataset from Appendix 7 to the FOCUS kinetics report (FOCUS Work Group on Degradation Kinetics 2014, 354).

    -
    library(mkin, quietly = TRUE)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
+
    +library(mkin, quietly = TRUE)
+LOD = 0.5
+FOCUS_2006_Z = data.frame(
+  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
+        42, 61, 96, 124),
+  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
+         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
+  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
+         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
+  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
+         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
+  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
+         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
 
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
    
+FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)

    Parent and one metabolite

    The next step is to set up the models used for the kinetic analysis. As the simultaneous fit of parent and the first metabolite is usually straightforward, Step 1 (SFO for parent only) is skipped here. We start with the model 2a, with formation and decline of metabolite Z1 and the pathway from parent directly to sink included (default in mkin).

    -
    Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
    +
    +Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+                Z1 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.2a)
    +
    +plot_sep(m.Z.2a)

    -
    summary(m.Z.2a, data = FALSE)$bpar
    +
    +summary(m.Z.2a, data = FALSE)$bpar
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
 ## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
 ## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
@@ -152,16 +158,20 @@
 ## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815

    As obvious from the parameter summary (the component of the summary), the kinetic rate constant from parent compound Z to sink is very small and the t-test for this parameter suggests that it is not significantly different from zero. This suggests, in agreement with the analysis in the FOCUS kinetics report, to simplify the model by removing the pathway to sink.

    A similar result can be obtained when formation fractions are used in the model formulation:

    -
    Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
    +
    +Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
+                   Z1 = mkinsub("SFO"),
+                   use_of_ff = "max")
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.2a.ff)
    +
    +plot_sep(m.Z.2a.ff)

    -
    summary(m.Z.2a.ff, data = FALSE)$bpar
    +
    +summary(m.Z.2a.ff, data = FALSE)$bpar
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
 ## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
 ## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
@@ -171,15 +181,19 @@
 
    Here, the ilr transformed formation fraction fitted in the model takes a very large value, and the backtransformed formation fraction from parent Z to Z1 is practically unity. Here, the covariance matrix used for the calculation of confidence intervals is not returned as the model is overparameterised.
    
 
    A simplified model is obtained by removing the pathway to the sink. 
    
 
    In the following, we use the parameterisation with formation fractions in order to be able to compare with the results in the FOCUS guidance, and as it makes it easier to use parameters obtained in a previous fit when adding a further metabolite.
    
-
    Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
+
    +Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    +m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
 
    ## Warning in mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    
-
    plot_sep(m.Z.3)
    
+
    +plot_sep(m.Z.3)
    
 
    
-
    summary(m.Z.3, data = FALSE)$bpar
    
+
    +summary(m.Z.3, data = FALSE)$bpar
    
 
    ##       Estimate se_notrans t value     Pr(>t)    Lower    Upper
 ## Z0_0  97.01488   2.597342  37.352 2.0106e-24 91.67597 102.3538
 ## k_Z0   2.23601   0.146904  15.221 9.1477e-15  1.95354   2.5593
@@ -191,51 +205,59 @@
 
    
 Metabolites Z2 and Z3
    
 
    As suggested in the FOCUS report, the pathway to sink was removed for metabolite Z1 as well in the next step. While this step appears questionable on the basis of the above results, it is followed here for the purpose of comparison. Also, in the FOCUS report, it is assumed that there is additional empirical evidence that Z1 quickly and exclusively hydrolyses to Z2.
    
-
    Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-               Z2 = mkinsub("SFO"), use_of_ff = "max")
    
+
    +Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+               Z2 = mkinsub("SFO"), use_of_ff = "max")
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    
+
    +m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    
 
    ## Warning in mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    
-
    plot_sep(m.Z.5)
    
+
    +plot_sep(m.Z.5)
    
 
    
 
    Finally, metabolite Z3 is added to the model. We use the optimised differential equation parameter values from the previous fit in order to accelerate the optimization.
    
-
    Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                   Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"),
-                   use_of_ff = "max")
    
+
    +Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                   Z2 = mkinsub("SFO", "Z3"),
+                   Z3 = mkinsub("SFO"),
+                   use_of_ff = "max")
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
    
+
    +m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
+                     parms.ini = m.Z.5$bparms.ode,
+                     quiet = TRUE)
    
 
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, :
 ## Observations with value of zero were removed from the data
    
 
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation did not converge:
 ## false convergence (8)
    
-
    plot_sep(m.Z.FOCUS)
    
+
    +plot_sep(m.Z.FOCUS)
    
 
    
-
    summary(m.Z.FOCUS, data = FALSE)$bpar
    
+
    +summary(m.Z.FOCUS, data = FALSE)$bpar
    
 
    ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.838721   1.994275 48.5584 4.0283e-42 92.826878 100.850563
-## k_Z0        2.215400   0.118459 18.7019 1.0414e-23  1.989462   2.466998
-## k_Z1        0.478301   0.028257 16.9267 6.2411e-22  0.424705   0.538662
-## k_Z2        0.451623   0.042138 10.7176 1.6313e-14  0.374336   0.544867
-## k_Z3        0.058694   0.015246  3.8499 1.7804e-04  0.034809   0.098967
-## f_Z2_to_Z3  0.471510   0.058352  8.0804 9.6640e-11  0.357775   0.588283
+## Z0_0       96.839001   1.994273 48.5585 4.0276e-42 92.827060 100.850943
+## k_Z0        2.215367   0.118456 18.7021 1.0410e-23  1.989432   2.466960
+## k_Z1        0.478310   0.028258 16.9265 6.2430e-22  0.424712   0.538673
+## k_Z2        0.451628   0.042139 10.7176 1.6313e-14  0.374337   0.544877
+## k_Z3        0.058692   0.015245  3.8498 1.7806e-04  0.034806   0.098972
+## f_Z2_to_Z3  0.471498   0.058350  8.0805 9.6614e-11  0.357741   0.588294
 ## sigma       3.984431   0.383402 10.3923 4.5575e-14  3.213126   4.755736
    
-
    endpoints(m.Z.FOCUS)
    
+
    +endpoints(m.Z.FOCUS)
    
 
    ## $ff
 ##   Z2_Z3 Z2_sink 
-## 0.47151 0.52849 
+##  0.4715  0.5285 
 ## 
 ## $distimes
 ##        DT50    DT90
 ## Z0  0.31288  1.0394
-## Z1  1.44919  4.8141
-## Z2  1.53479  5.0985
-## Z3 11.80955 39.2305
    
+## Z1  1.44916  4.8140
+## Z2  1.53478  5.0984
+## Z3 11.80983 39.2314
    
 
    This fit corresponds to the final result chosen in Appendix 7 of the FOCUS report. Confidence intervals returned by mkin are based on internally transformed parameters, however.
    @@ -243,90 +265,101 @@ Using the SFORB model

    As the FOCUS report states, there is a certain tailing of the time course of metabolite Z3. Also, the time course of the parent compound is not fitted very well using the SFO model, as residues at a certain low level remain.

    Therefore, an additional model is offered here, using the single first-order reversible binding (SFORB) model for metabolite Z3. As expected, the \(\chi^2\) error level is lower for metabolite Z3 using this model and the graphical fit for Z3 is improved. However, the covariance matrix is not returned.

    -
    Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    +
    +Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFORB"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.mkin.1)
    +
    +plot_sep(m.Z.mkin.1)

    -
    summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
    +
    +summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
    ## NULL

    Therefore, a further stepwise model building is performed starting from the stage of parent and two metabolites, starting from the assumption that the model fit for the parent compound can be improved by using the SFORB model.

    -
    Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
    +
    +Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    +
    +m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
 ## value of zero were removed from the data
    -
    plot_sep(m.Z.mkin.3)
    +
    +plot_sep(m.Z.mkin.3)

    This results in a much better representation of the behaviour of the parent compound Z0.

    Finally, Z3 is added as well. These models appear overparameterised (no covariance matrix returned) if the sink for Z1 is left in the models.

    -
    Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
    +
    +Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
    +
    +m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
+                      parms.ini = m.Z.mkin.3$bparms.ode,
+                      quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
 ## 3$bparms.ode, : Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
-## 3$bparms.ode, : Shapiro-Wilk test for standardized residuals: p = 0.0449
    -
    plot_sep(m.Z.mkin.4)
    +
    +plot_sep(m.Z.mkin.4)

    The error level of the fit, but especially of metabolite Z3, can be improved if the SFORB model is chosen for this metabolite, as this model is capable of representing the tailing of the metabolite decline phase.

    -
    Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    +
    +Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
+                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
+                    Z2 = mkinsub("SFO", "Z3"),
+                    Z3 = mkinsub("SFORB"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
    +
    +m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
+                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
+                      quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
 ## 4$bparms.ode[1:4], : Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = m.Z.mkin.
-## 4$bparms.ode[1:4], : Shapiro-Wilk test for standardized residuals: p = 0.00785
    -
    plot_sep(m.Z.mkin.5)
    +
    +plot_sep(m.Z.mkin.5)

    The summary view of the backtransformed parameters shows that we get no confidence intervals due to overparameterisation. As the optimized is excessively small, it seems reasonable to fix it to zero.

    -
    m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
    +
    +m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
+                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
+                                     k_Z3_bound_free = 0),
+                       fixed_parms = "k_Z3_bound_free",
+                       quiet = TRUE)
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = c(m.Z.mkin.
 ## 5$bparms.ode[1:7], : Observations with value of zero were removed from the data
    -
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini = c(m.Z.mkin.
-## 5$bparms.ode[1:7], : Shapiro-Wilk test for standardized residuals: p = 0.00785
    -
    plot_sep(m.Z.mkin.5a)
    +
    +plot_sep(m.Z.mkin.5a)

    As expected, the residual plots for Z0 and Z3 are more random than in the case of the all SFO model for which they were shown above. In conclusion, the model is proposed as the best-fit model for the dataset from Appendix 7 of the FOCUS report.

    A graphical representation of the confidence intervals can finally be obtained.

    -
    mkinparplot(m.Z.mkin.5a)
    +
    +mkinparplot(m.Z.mkin.5a)

    The endpoints obtained with this model are

    -
    endpoints(m.Z.mkin.5a)
    +
    +endpoints(m.Z.mkin.5a)
    ## $ff
 ## Z0_free   Z2_Z3 Z2_sink Z3_free 
 ## 1.00000 0.53656 0.46344 1.00000 
 ## 
 ## $SFORB
 ##     Z0_b1     Z0_b2     Z3_b1     Z3_b2 
-## 2.4471358 0.0075126 0.0800073 0.0000000 
+## 2.4471371 0.0075126 0.0800070 0.0000000 
 ## 
 ## $distimes
 ##      DT50   DT90 DT50back DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
 ## Z0 0.3043 1.1848  0.35666    0.28325     92.265         NA         NA
 ## Z1 1.5148 5.0320       NA         NA         NA         NA         NA
-## Z2 1.6414 5.4526       NA         NA         NA         NA         NA
+## Z2 1.6414 5.4525       NA         NA         NA         NA         NA
 ## Z3     NA     NA       NA         NA         NA     8.6636        Inf

    It is clear the degradation rate of Z3 towards the end of the experiment is very low as DT50_Z3_b2 (the second Eigenvalue of the system of two differential equations representing the SFORB system for Z3, corresponding to the slower rate constant of the DFOP model) is reported to be infinity. However, this appears to be a feature of the data.

    @@ -357,7 +390,7 @@
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css new file mode 100644 index 00000000..07aee5fc --- /dev/null +++ b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.css @@ -0,0 +1,4 @@ +/* Styles for section anchors */ +a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} +a.anchor-section::before {content: '#';} +.hasAnchor:hover a.anchor-section {visibility: visible;} diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js new file mode 100644 index 00000000..570f99a0 --- /dev/null +++ b/docs/dev/articles/web_only/FOCUS_Z_files/anchor-sections-1.0/anchor-sections.js @@ -0,0 +1,33 @@ +// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020. +document.addEventListener('DOMContentLoaded', function() { + // Do nothing if AnchorJS is used + if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) { + return; + } + + const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6'); + + // Do nothing if sections are already anchored + if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) { + return null; + } + + // Use section id when pandoc runs with --section-divs + const section_id = function(x) { + return ((x.classList.contains('section') || (x.tagName === 'SECTION')) + ? x.id : ''); + }; + + // Add anchors + h.forEach(function(x) { + const id = x.id || section_id(x.parentElement); + if (id === '') { + return null; + } + let anchor = document.createElement('a'); + anchor.href = '#' + id; + anchor.classList = ['anchor-section']; + x.classList.add('hasAnchor'); + x.appendChild(anchor); + }); +}); diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png index 23d051ce..575def46 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_1-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png index d3702fb6..22305ab1 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png index 4a6fce4f..2213f493 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png index dd6537b7..fc5e5556 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png index b986c30b..5c29341c 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png index 23d051ce..575def46 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_2-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png index 6e9f4efa..98ce34a7 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_3-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png index 146acea9..d04a411e 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png index 47d806c0..29a74490 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png index 7db8b07d..0acfa2a4 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_7-1.png differ diff --git a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png index 0c698299..ca191b00 100644 Binary files a/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png and b/docs/dev/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png differ diff --git a/docs/dev/articles/web_only/NAFTA_examples.html b/docs/dev/articles/web_only/NAFTA_examples.html index ebe4b84e..c3192b37 100644 --- a/docs/dev/articles/web_only/NAFTA_examples.html +++ b/docs/dev/articles/web_only/NAFTA_examples.html @@ -95,13 +95,14 @@ -
    + +

    Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance

    Johannes Ranke

    -

    2020-10-15

    +

    2020-11-19

    Source: vignettes/web_only/NAFTA_examples.rmd @@ -123,15 +124,15 @@

    Example on page 5, upper panel

    -
    -p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    +
    +p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p5a)
    +
    +plot(p5a)

    -
    -print(p5a)
    +
    +print(p5a)
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 465.21753  56.27506  32.06401 
@@ -157,7 +158,7 @@
 ##          Estimate   Pr(>t)   Lower    Upper
 ## parent_0 9.99e+01 1.41e-26 98.8116 101.0810
 ## k1       2.67e-02 5.05e-06  0.0243   0.0295
-## k2       2.17e-12 5.00e-01  0.0000      Inf
+## k2       2.42e-12 5.00e-01  0.0000      Inf
 ## g        6.47e-01 3.67e-06  0.6248   0.6677
 ## sigma    1.27e+00 8.91e-06  0.8395   1.6929
 ## 
@@ -166,7 +167,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  67.7 2.25e+02 6.77e+01
 ## IORE 58.2 1.07e+03 3.22e+02
-## DFOP 55.5 5.83e+11 3.20e+11
+## DFOP 55.5 5.22e+11 2.86e+11
 ## 
 ## Representative half-life:
 ## [1] 321.51
    @@ -174,15 +175,15 @@

    Example on page 5, lower panel

    -
    -p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    +
    +p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p5b)
    +
    +plot(p5b)

    -
    -print(p5b)
    +
    +print(p5b)
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 94.81123 10.10936  7.55871 
@@ -208,7 +209,7 @@
 ##          Estimate   Pr(>t)   Lower   Upper
 ## parent_0 9.84e+01 1.24e-27 97.8078 98.9187
 ## k1       1.55e-02 4.10e-04  0.0143  0.0167
-## k2       1.04e-11 5.00e-01  0.0000     Inf
+## k2       1.10e-11 5.00e-01  0.0000     Inf
 ## g        6.89e-01 2.92e-03  0.6626  0.7142
 ## sigma    6.48e-01 2.38e-05  0.4147  0.8813
 ## 
@@ -217,7 +218,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  86.6 2.88e+02 8.66e+01
 ## IORE 85.5 7.17e+02 2.16e+02
-## DFOP 83.6 1.09e+11 6.67e+10
+## DFOP 83.6 1.03e+11 6.29e+10
 ## 
 ## Representative half-life:
 ## [1] 215.87
    @@ -225,15 +226,15 @@

    Example on page 6

    -
    -p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    +
    +p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p6)
    +
    +plot(p6)

    -
    -print(p6)
    +
    +print(p6)
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 188.45361  51.00699  42.46931 
@@ -259,7 +260,7 @@
 ##          Estimate   Pr(>t)   Lower   Upper
 ## parent_0 9.66e+01 1.57e-25 95.3476 97.8979
 ## k1       2.55e-02 7.33e-06  0.0233  0.0278
-## k2       3.88e-11 5.00e-01  0.0000     Inf
+## k2       3.60e-11 5.00e-01  0.0000     Inf
 ## g        8.61e-01 7.55e-06  0.8314  0.8867
 ## sigma    1.46e+00 6.93e-06  0.9661  1.9483
 ## 
@@ -268,7 +269,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  38.6 1.28e+02 3.86e+01
 ## IORE 34.0 1.77e+02 5.32e+01
-## DFOP 34.1 8.42e+09 1.79e+10
+## DFOP 34.1 9.07e+09 1.93e+10
 ## 
 ## Representative half-life:
 ## [1] 53.17
    @@ -276,15 +277,15 @@

    Example on page 7

    -
    -p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    +
    +p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p7)
    +
    +plot(p7)

    -
    -print(p7)
    +
    +print(p7)
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 3661.661 3195.030 3174.145 
@@ -310,7 +311,7 @@
 ##          Estimate   Pr(>t)   Lower    Upper
 ## parent_0 9.89e+01 9.44e-49 95.4640 102.2573
 ## k1       1.81e-02 1.75e-01  0.0116   0.0281
-## k2       2.30e-10 5.00e-01  0.0000      Inf
+## k2       2.89e-10 5.00e-01  0.0000      Inf
 ## g        6.06e-01 2.19e-01  0.4826   0.7178
 ## sigma    7.40e+00 2.97e-15  6.0201   8.7754
 ## 
@@ -319,7 +320,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  94.3 3.13e+02 9.43e+01
 ## IORE 96.7 1.51e+03 4.55e+02
-## DFOP 96.4 5.95e+09 3.01e+09
+## DFOP 96.4 4.75e+09 2.40e+09
 ## 
 ## Representative half-life:
 ## [1] 454.55
    @@ -332,15 +333,15 @@

    Example on page 8

    For this dataset, the IORE fit does not converge when the default starting values used by mkin for the IORE model are used. Therefore, a lower value for the rate constant is used here.

    -
    -p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    +
    +p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    ## The half-life obtained from the IORE model may be used
    -
    -plot(p8)
    +
    +plot(p8)

    -
    -print(p8)
    +
    +print(p8)
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 1996.9408  444.9237  547.5616 
@@ -387,15 +388,15 @@
 
    
 
    
 Example on page 9, upper panel
    
-
    -p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    
+
    +p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p9a)
    
+
    +plot(p9a)
    
 
    
-
    -print(p9a)
    
+
    +print(p9a)
    
 
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 839.35238  88.57064   9.93363 
@@ -421,7 +422,7 @@
 ##          Estimate   Pr(>t)  Lower  Upper
 ## parent_0 9.85e+01 2.54e-20 97.390 99.672
 ## k1       1.38e-01 3.52e-05  0.131  0.146
-## k2       6.69e-13 5.00e-01  0.000    Inf
+## k2       9.03e-13 5.00e-01  0.000    Inf
 ## g        6.52e-01 8.13e-06  0.642  0.661
 ## sigma    7.88e-01 6.13e-02  0.481  1.095
 ## 
@@ -430,7 +431,7 @@
 ##      DT50     DT90 DT50_rep
 ## SFO  16.9 5.63e+01 1.69e+01
 ## IORE 11.6 3.37e+02 1.01e+02
-## DFOP 10.5 1.86e+12 1.04e+12
+## DFOP 10.5 1.38e+12 7.67e+11
 ## 
 ## Representative half-life:
 ## [1] 101.43
    
@@ -439,15 +440,19 @@
 
    
 
    
 Example on page 9, lower panel
    
-
    -p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    
+
    +p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    
+
    ## Warning in sqrt(diag(covar)): NaNs produced
    
+
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
+
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p9b)
    
+
    +plot(p9b)
    
 
    
-
    -print(p9b)
    
+
    +print(p9b)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 35.64867 23.22334 35.64867 
@@ -470,12 +475,12 @@
 ## sigma             1.288 1.76e-04  0.7456  1.830
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  94.7123 1.61e-16 93.1355 96.2891
-## k1         0.0389 1.43e-06  0.0312  0.0485
-## k2         0.0389 6.67e-03  0.0186  0.0812
-## g          0.7742 5.00e-01  0.0000  1.0000
-## sigma      1.5957 2.50e-04  0.9135  2.2779
+##          Estimate Pr(>t)   Lower   Upper
+## parent_0  94.7123     NA 93.1355 96.2891
+## k1         0.0389     NA  0.0266  0.0569
+## k2         0.0389     NA  0.0255  0.0592
+## g          0.5256     NA      NA      NA
+## sigma      1.5957     NA  0.9135  2.2779
 ## 
 ## 
 ## DTx values:
@@ -491,15 +496,16 @@
 
    
 
    
 Example on page 10
    
-
    -p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    
+
    +p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    
+
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p10)
    
+
    +plot(p10)
    
 
    
-
    -print(p10)
    
+
    +print(p10)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 899.4089 336.4348 899.4089 
@@ -522,12 +528,12 @@
 ## sigma              4.90 1.77e-04  2.837   6.968
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0 101.7315 1.41e-09 91.6534 111.810
-## k1         0.0495 6.48e-04  0.0303   0.081
-## k2         0.0495 1.67e-02  0.0201   0.122
-## g          0.6634 5.00e-01  0.0000   1.000
-## sigma      8.0152 2.50e-04  4.5886  11.442
+##          Estimate   Pr(>t)   Lower    Upper
+## parent_0 101.7315 1.41e-09 91.6534 111.8097
+## k1         0.0495 5.63e-03  0.0240   0.1020
+## k2         0.0495 1.93e-03  0.0272   0.0903
+## g          0.4487      NaN  0.0000   1.0000
+## sigma      8.0152 2.50e-04  4.5886  11.4418
 ## 
 ## 
 ## DTx values:
@@ -547,15 +553,15 @@
 
    
 
    
 Example on page 11
    
-
    -p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    
+
    +p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p11)
    
+
    +plot(p11)
    
 
    
-
    -print(p11)
    
+
    +print(p11)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 579.6805 204.7932 144.7783 
@@ -581,7 +587,7 @@
 ##          Estimate   Pr(>t)    Lower    Upper
 ## parent_0 1.05e+02 9.47e-13  99.9990 109.1224
 ## k1       4.41e-02 5.95e-03   0.0296   0.0658
-## k2       7.25e-13 5.00e-01   0.0000      Inf
+## k2       9.94e-13 5.00e-01   0.0000      Inf
 ## g        3.22e-01 1.45e-03   0.2814   0.3650
 ## sigma    3.22e+00 3.52e-04   1.8410   4.5906
 ## 
@@ -590,7 +596,7 @@
 ##          DT50     DT90 DT50_rep
 ## SFO  2.16e+02 7.18e+02 2.16e+02
 ## IORE 9.73e+02 1.37e+08 4.11e+07
-## DFOP 4.21e+11 2.64e+12 9.56e+11
+## DFOP 3.07e+11 1.93e+12 6.97e+11
 ## 
 ## Representative half-life:
 ## [1] 41148171
    
@@ -604,17 +610,20 @@
 
    
 
    
 Example on page 12, upper panel
    
-
    -p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    
+
    +p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    
 
    ## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
+## matrix
+
+## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
 ## matrix
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p12a)
    
+
    +plot(p12a)
    
 
    
-
    -print(p12a)
    
+
    +print(p12a)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 695.4440 220.0685 695.4440 
@@ -637,12 +646,12 @@
 ## sigma             3.965     NA    NA    NA
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  100.521 2.74e-10 92.2366 108.805
-## k1          0.124 5.75e-06  0.0958   0.161
-## k2          0.124 6.72e-02  0.0319   0.484
-## g           0.877 5.00e-01  0.0000   1.000
-## sigma       7.048 2.50e-04  4.0349  10.061
+##          Estimate   Pr(>t) Lower Upper
+## parent_0  100.521 2.74e-10    NA    NA
+## k1          0.124 2.53e-05    NA    NA
+## k2          0.124 2.52e-02    NA    NA
+## g           0.793 5.00e-01    NA    NA
+## sigma       7.048 2.50e-04    NA    NA
 ## 
 ## 
 ## DTx values:
@@ -657,23 +666,21 @@
 
    
 
    
 Example on page 12, lower panel
    
-
    -p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    
+
    +p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    
 
    ## Warning in sqrt(diag(covar)): NaNs produced
    
 
    ## Warning in qt(alpha/2, rdf): NaNs produced
    
 
    ## Warning in qt(1 - alpha/2, rdf): NaNs produced
    
-
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
-
    ## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
    
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p12b)
    
+
    +plot(p12b)
    
 
    
-
    -print(p12b)
    
+
    +print(p12b)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 58.90242 19.06353 58.90242 
@@ -697,11 +704,11 @@
 ## 
 ## $DFOP
 ##          Estimate Pr(>t) Lower Upper
-## parent_0  97.6840    NaN   NaN   NaN
-## k1         0.0589    NaN    NA    NA
-## k2         0.0589    NaN    NA    NA
-## g          0.6902    NaN    NA    NA
-## sigma      3.4323    NaN   NaN   NaN
+## parent_0  97.6840     NA   NaN   NaN
+## k1         0.0589     NA    NA    NA
+## k2         0.0589     NA    NA    NA
+## g          0.6473     NA    NA    NA
+## sigma      3.4323     NA   NaN   NaN
 ## 
 ## 
 ## DTx values:
@@ -716,15 +723,19 @@
 
    
 
    
 Example on page 13
    
-
    -p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    
+
    +p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    
+
    ## Warning in sqrt(diag(covar)): NaNs produced
    
+
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
+
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p13)
    
+
    +plot(p13)
    
 
    
-
    -print(p13)
    
+
    +print(p13)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 174.5971 142.3951 174.5971 
@@ -747,12 +758,12 @@
 ## sigma            3.0811 9.64e-05  1.84296  4.319
 ## 
 ## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 92.73500 9.25e-15 8.95e+01 9.59e+01
-## k1        0.00258 4.28e-01 1.45e-08 4.61e+02
-## k2        0.00258 3.69e-08 2.20e-03 3.03e-03
-## g         0.00442 5.00e-01 0.00e+00 1.00e+00
-## sigma     3.41172 1.35e-04 2.02e+00 4.80e+00
+##          Estimate Pr(>t)    Lower    Upper
+## parent_0 92.73500     NA 8.95e+01 95.92118
+## k1        0.00258     NA 4.25e-04  0.01569
+## k2        0.00258     NA 1.76e-03  0.00379
+## g         0.16452     NA       NA       NA
+## sigma     3.41172     NA 2.02e+00  4.79960
 ## 
 ## 
 ## DTx values:
@@ -768,19 +779,19 @@
 
    
 
    
 DT50 not observed in the study and DFOP problems in PestDF
    
-
    -p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    
+
    +p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    
 
    ## Warning in sqrt(diag(covar)): NaNs produced
    
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p14)
    
+
    +plot(p14)
    
 
    
-
    -print(p14)
    
+
    +print(p14)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 48.43249 28.67746 27.26248 
@@ -806,7 +817,7 @@
 ##          Estimate   Pr(>t)    Lower    Upper
 ## parent_0 1.00e+02 2.96e-28 99.40280 101.2768
 ## k1       9.53e-03 1.20e-01  0.00638   0.0143
-## k2       7.70e-12 5.00e-01  0.00000      Inf
+## k2       5.33e-12 5.00e-01  0.00000      Inf
 ## g        3.98e-01 2.19e-01  0.30481   0.4998
 ## sigma    1.17e+00 7.68e-06  0.77406   1.5610
 ## 
@@ -815,7 +826,7 @@
 ##          DT50     DT90 DT50_rep
 ## SFO  2.48e+02 8.25e+02 2.48e+02
 ## IORE 4.34e+02 2.22e+04 6.70e+03
-## DFOP 2.41e+10 2.33e+11 9.00e+10
+## DFOP 3.48e+10 3.37e+11 1.30e+11
 ## 
 ## Representative half-life:
 ## [1] 6697.44
    
@@ -824,19 +835,15 @@
 
    
 
    
 N is less than 1 and DFOP fraction parameter is below zero
    
-
    -p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
-## doubtful
    
+
    +p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p15a)
    
+
    +plot(p15a)
    
 
    
-
    -print(p15a)
    
+
    +print(p15a)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 245.5248 135.0132 245.5248 
@@ -860,10 +867,10 @@
 ## 
 ## $DFOP
 ##          Estimate Pr(>t)    Lower    Upper
-## parent_0 97.96752     NA 94.21914 101.7159
-## k1        0.00952     NA  0.00241   0.0377
-## k2        0.00952     NA  0.00747   0.0121
-## g         0.17247     NA       NA       NA
+## parent_0 97.96751     NA 94.21913 101.7159
+## k1        0.00952     NA  0.00221   0.0411
+## k2        0.00952     NA  0.00626   0.0145
+## g         0.21241     NA  0.00000   1.0000
 ## sigma     4.18778     NA  2.39747   5.9781
 ## 
 ## 
@@ -875,19 +882,19 @@
 ## 
 ## Representative half-life:
 ## [1] 41.33
    
-
    -p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
    
+
    +p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
    
 
    ## Warning in sqrt(diag(covar)): NaNs produced
    
 
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
 
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
 ## doubtful
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p15b)
    
+
    +plot(p15b)
    
 
    
-
    -print(p15b)
    
+
    +print(p15b)
    
 
    ## Sums of squares:
 ##       SFO      IORE      DFOP 
 ## 106.91629  68.55574 106.91629 
@@ -911,11 +918,11 @@
 ## 
 ## $DFOP
 ##          Estimate Pr(>t)    Lower    Upper
-## parent_0 1.01e+02     NA 98.24464 1.04e+02
-## k1       4.86e-03     NA  0.00068 3.47e-02
-## k2       4.86e-03     NA  0.00338 6.99e-03
-## g        1.50e-01     NA       NA       NA
-## sigma    2.76e+00     NA  1.58208 3.94e+00
+## parent_0 1.01e+02     NA 9.82e+01 1.04e+02
+## k1       4.86e-03     NA 8.63e-04 2.73e-02
+## k2       4.86e-03     NA 3.21e-03 7.35e-03
+## g        1.88e-01     NA       NA       NA
+## sigma    2.76e+00     NA 1.58e+00 3.94e+00
 ## 
 ## 
 ## DTx values:
@@ -931,17 +938,17 @@
 
    
 
    
 The DFOP fraction parameter is greater than 1
    
-
    -p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    
+
    +p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    
 
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
 
    ## The representative half-life of the IORE model is longer than the one corresponding
    
 
    ## to the terminal degradation rate found with the DFOP model.
    
 
    ## The representative half-life obtained from the DFOP model may be used
    
-
    -plot(p16)
    
+
    +plot(p16)
    
 
    
-
    -print(p16)
    
+
    +print(p16)
    
 
    ## Sums of squares:
 ##      SFO     IORE     DFOP 
 ## 3831.804 2062.008 1550.980 
@@ -966,7 +973,7 @@
 ## $DFOP
 ##          Estimate   Pr(>t)   Lower  Upper
 ## parent_0  88.5333 7.40e-18 79.9836 97.083
-## k1        18.5560 5.00e-01  0.0000    Inf
+## k1        18.8461 5.00e-01  0.0000    Inf
 ## k2         0.0776 1.41e-05  0.0518  0.116
 ## g          0.4733 1.41e-09  0.3674  0.582
 ## sigma      7.1902 2.11e-08  5.2785  9.102
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css
new file mode 100644
index 00000000..07aee5fc
--- /dev/null
+++ b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.css
@@ -0,0 +1,4 @@
+/* Styles for section anchors */
+a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
+a.anchor-section::before {content: '#';}
+.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js
new file mode 100644
index 00000000..570f99a0
--- /dev/null
+++ b/docs/dev/articles/web_only/NAFTA_examples_files/anchor-sections-1.0/anchor-sections.js
@@ -0,0 +1,33 @@
+// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
+document.addEventListener('DOMContentLoaded', function() {
+  // Do nothing if AnchorJS is used
+  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
+    return;
+  }
+
+  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
+
+  // Do nothing if sections are already anchored
+  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
+    return null;
+  }
+
+  // Use section id when pandoc runs with --section-divs
+  const section_id = function(x) {
+    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
+            ? x.id : '');
+  };
+
+  // Add anchors
+  h.forEach(function(x) {
+    const id = x.id || section_id(x.parentElement);
+    if (id === '') {
+      return null;
+    }
+    let anchor = document.createElement('a');
+    anchor.href = '#' + id;
+    anchor.classList = ['anchor-section'];
+    x.classList.add('hasAnchor');
+    x.appendChild(anchor);
+  });
+});
diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png
index 3e9c743f..38b251ea 100644
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index 029e6a17..ce177190 100644
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diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p16-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p16-1.png
index f3fa460e..b61f28e2 100644
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diff --git a/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png b/docs/dev/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png
index d6ae1fa4..515e9095 100644
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diff --git a/docs/dev/articles/web_only/benchmarks.html b/docs/dev/articles/web_only/benchmarks.html
index 5105afcd..ff70847e 100644
--- a/docs/dev/articles/web_only/benchmarks.html
+++ b/docs/dev/articles/web_only/benchmarks.html
@@ -102,7 +102,7 @@
       
    Benchmark timings for mkin
    
                         
    Johannes Ranke
    
             
-            
    2020-11-06
    
+            
    2020-11-19
    
       
       Source: vignettes/web_only/benchmarks.rmd
       
@@ -116,17 +116,17 @@
 
    
 Test cases
    
 
    Parent only:
    
-
    -FOCUS_C <- FOCUS_2006_C
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
+
    +FOCUS_C <- FOCUS_2006_C
+FOCUS_D <- subset(FOCUS_2006_D, value != 0)
 parent_datasets <- list(FOCUS_C, FOCUS_D)
 
 t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets))[["elapsed"]]
 t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets,
-    error_model = "tc"))[["elapsed"]]
    
+    error_model = "tc"))[["elapsed"]]
    
 
    One metabolite:
    
-
    -SFO_SFO <- mkinmod(
+
    +SFO_SFO <- mkinmod(
   parent = mkinsub("SFO", "m1"),
   m1 = mkinsub("SFO"))
 FOMC_SFO <- mkinmod(
@@ -137,18 +137,18 @@
   m1 = mkinsub("SFO"))
 t3 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D)))[["elapsed"]]
 t4 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
-    error_model = "tc"))[["elapsed"]]
    
+    error_model = "tc"))[["elapsed"]]
    
 
    ## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...): Optimisation did not converge:
 ## iteration limit reached without convergence (10)
 
 ## Warning in mkinfit(models[[model_index]], datasets[[dataset_index]], ...): Optimisation did not converge:
 ## iteration limit reached without convergence (10)
    
-
    -t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
-    error_model = "obs"))[["elapsed"]]
    
+
    +t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
+    error_model = "obs"))[["elapsed"]]
    
 
    Two metabolites, synthetic data:
    
-
    -m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
+
    +m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
                            M1 = mkinsub("SFO", "M2"),
                            M2 = mkinsub("SFO"),
                            use_of_ff = "max", quiet = TRUE)
@@ -173,11 +173,11 @@
 t10 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a),
     error_model = "obs"))[["elapsed"]]
 t11 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c),
-    error_model = "obs"))[["elapsed"]]
    
-
    -mkin_benchmarks[system_string, paste0("t", 1:11)] <-
+    error_model = "obs"))[["elapsed"]]
    
+
    +mkin_benchmarks[system_string, paste0("t", 1:11)] <-
   c(t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11)
-save(mkin_benchmarks, file = "~/git/mkin/vignettes/web_only/mkin_benchmarks.rda")
    
+save(mkin_benchmarks, file = "~/git/mkin/vignettes/web_only/mkin_benchmarks.rda")
    
 
    
 
    
 
    
@@ -232,8 +232,8 @@
 
 
 0.9.50.4
-1.753
-3.791
+1.702
+3.717
 
 
 
@@ -294,9 +294,9 @@
 
 
 0.9.50.4
-1.374
-6.974
-2.735
+1.355
+7.015
+2.729
 
 
 
@@ -381,12 +381,12 @@
 
 
 0.9.50.4
-0.766
-1.250
+0.759
+1.245
 1.436
-3.749
-1.878
-2.879
+3.687
+1.886
+3.028
 
 
 
diff --git a/docs/dev/articles/web_only/compiled_models.html b/docs/dev/articles/web_only/compiled_models.html
index 055d0646..3d1c7fcd 100644
--- a/docs/dev/articles/web_only/compiled_models.html
+++ b/docs/dev/articles/web_only/compiled_models.html
@@ -32,7 +32,7 @@
       
       
         mkin
-        0.9.50.3
+        0.9.50.4
       
     
    
 
@@ -80,7 +80,7 @@
  • - + @@ -95,15 +95,16 @@ -
    + +

    Performance benefit by using compiled model definitions in mkin

    Johannes Ranke

    -

    2020-10-08

    +

    2020-11-19

    - Source: vignettes/web_only/compiled_models.rmd + Source: vignettes/web_only/compiled_models.rmd
    @@ -114,79 +115,86 @@

    How to benefit from compiled models

    When using an mkin version equal to or greater than 0.9-36 and a C compiler is available, you will see a message that the model is being compiled from autogenerated C code when defining a model using mkinmod. Starting from version 0.9.49.9, the mkinmod() function checks for presence of a compiler using

    -
    pkgbuild::has_compiler()
    +
    +pkgbuild::has_compiler()

    In previous versions, it used Sys.which("gcc") for this check.

    On Linux, you need to have the essential build tools like make and gcc or clang installed. On Debian based linux distributions, these will be pulled in by installing the build-essential package.

    On MacOS, which I do not use personally, I have had reports that a compiler is available by default.

    On Windows, you need to install Rtools and have the path to its bin directory in your PATH variable. You do not need to modify the PATH variable when installing Rtools. Instead, I would recommend to put the line

    -
    Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";"))
    +
    +Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";"))

    into your .Rprofile startup file. This is just a text file with some R code that is executed when your R session starts. It has to be named .Rprofile and has to be located in your home directory, which will generally be your Documents folder. You can check the location of the home directory used by R by issuing

    -
    Sys.getenv("HOME")
    +
    +Sys.getenv("HOME")

    Comparison with other solution methods

    First, we build a simple degradation model for a parent compound with one metabolite, and we remove zero values from the dataset.

    -
    library("mkin", quietly = TRUE)
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    +
    +library("mkin", quietly = TRUE)
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
    ## Successfully compiled differential equation model from auto-generated C code.
    -
    FOCUS_D <- subset(FOCUS_2006_D, value != 0)
    +
    +FOCUS_D <- subset(FOCUS_2006_D, value != 0)

    We can compare the performance of the Eigenvalue based solution against the compiled version and the R implementation of the differential equations using the benchmark package. In the output of below code, the warnings about zero being removed from the FOCUS D dataset are suppressed. Since mkin version 0.9.49.11, an analytical solution is also implemented, which is included in the tests below.

    -
    if (require(rbenchmark)) {
-  b.1 <- benchmark(
-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "deSolve",
-       use_compiled = FALSE, quiet = TRUE),
-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "eigen", quiet = TRUE),
-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "deSolve", quiet = TRUE),
-    "analytical" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "analytical",
-       use_compiled = FALSE, quiet = TRUE),
-    replications = 1, order = "relative",
-    columns = c("test", "replications", "relative", "elapsed"))
-  print(b.1)
-} else {
-  print("R package rbenchmark is not available")
-}
    +
    +if (require(rbenchmark)) {
+  b.1 <- benchmark(
+    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "deSolve",
+       use_compiled = FALSE, quiet = TRUE),
+    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "eigen", quiet = TRUE),
+    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "deSolve", quiet = TRUE),
+    "analytical" = mkinfit(SFO_SFO, FOCUS_D,
+       solution_type = "analytical",
+       use_compiled = FALSE, quiet = TRUE),
+    replications = 1, order = "relative",
+    columns = c("test", "replications", "relative", "elapsed"))
+  print(b.1)
+} else {
+  print("R package rbenchmark is not available")
+}
    ##                    test replications relative elapsed
-## 4            analytical            1    1.000   0.195
-## 3     deSolve, compiled            1    1.769   0.345
-## 2      Eigenvalue based            1    2.087   0.407
-## 1 deSolve, not compiled            1   42.656   8.318
    +## 4 analytical 1 1.000 0.186 +## 3 deSolve, compiled 1 1.742 0.324 +## 2 Eigenvalue based 1 2.048 0.381 +## 1 deSolve, not compiled 1 42.532 7.911

    We see that using the compiled model is by more than a factor of 10 faster than using deSolve without compiled code.

    Model without analytical solution

    This evaluation is also taken from the example section of mkinfit. No analytical solution is available for this system, and now Eigenvalue based solution is possible, so only deSolve using with or without compiled code is available.

    -
    if (require(rbenchmark)) {
-  FOMC_SFO <- mkinmod(
-    parent = mkinsub("FOMC", "m1"),
-    m1 = mkinsub( "SFO"))
-
-  b.2 <- benchmark(
-    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D,
-                                      use_compiled = FALSE, quiet = TRUE),
-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE),
-    replications = 1, order = "relative",
-    columns = c("test", "replications", "relative", "elapsed"))
-  print(b.2)
-  factor_FOMC_SFO <- round(b.2["1", "relative"])
-} else {
-  factor_FOMC_SFO <- NA
-  print("R package benchmark is not available")
-}
    +
    +if (require(rbenchmark)) {
+  FOMC_SFO <- mkinmod(
+    parent = mkinsub("FOMC", "m1"),
+    m1 = mkinsub( "SFO"))
+
+  b.2 <- benchmark(
+    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D,
+                                      use_compiled = FALSE, quiet = TRUE),
+    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE),
+    replications = 1, order = "relative",
+    columns = c("test", "replications", "relative", "elapsed"))
+  print(b.2)
+  factor_FOMC_SFO <- round(b.2["1", "relative"])
+} else {
+  factor_FOMC_SFO <- NA
+  print("R package benchmark is not available")
+}
    ## Successfully compiled differential equation model from auto-generated C code.
    ##                    test replications relative elapsed
-## 2     deSolve, compiled            1    1.000   0.474
-## 1 deSolve, not compiled            1   30.909  14.651
    +## 2 deSolve, compiled 1 1.000 0.465 +## 1 deSolve, not compiled 1 30.852 14.346

    Here we get a performance benefit of a factor of 31 using the version of the differential equation model compiled from C code!

    -

    This vignette was built with mkin 0.9.50.3 on

    -
    ## R version 4.0.2 (2020-06-22)
+
    This vignette was built with mkin 0.9.50.4 on
    
+
    ## R version 4.0.3 (2020-10-10)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 10 (buster)
    
 
    ## CPU model: AMD Ryzen 7 1700 Eight-Core Processor
    
@@ -208,7 +216,7 @@
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css new file mode 100644 index 00000000..07aee5fc --- /dev/null +++ b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css @@ -0,0 +1,4 @@ +/* Styles for section anchors */ +a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} +a.anchor-section::before {content: '#';} +.hasAnchor:hover a.anchor-section {visibility: visible;} diff --git a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js new file mode 100644 index 00000000..570f99a0 --- /dev/null +++ b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js @@ -0,0 +1,33 @@ +// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020. +document.addEventListener('DOMContentLoaded', function() { + // Do nothing if AnchorJS is used + if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) { + return; + } + + const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6'); + + // Do nothing if sections are already anchored + if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) { + return null; + } + + // Use section id when pandoc runs with --section-divs + const section_id = function(x) { + return ((x.classList.contains('section') || (x.tagName === 'SECTION')) + ? x.id : ''); + }; + + // Add anchors + h.forEach(function(x) { + const id = x.id || section_id(x.parentElement); + if (id === '') { + return null; + } + let anchor = document.createElement('a'); + anchor.href = '#' + id; + anchor.classList = ['anchor-section']; + x.classList.add('hasAnchor'); + x.appendChild(anchor); + }); +}); diff --git a/docs/dev/news/index.html b/docs/dev/news/index.html index 3a868426..b8577da0 100644 --- a/docs/dev/news/index.html +++ b/docs/dev/news/index.html @@ -146,6 +146,10 @@ mkin 0.9.50.4 (unreleased) Unreleased
      +

    • ‘f_norm_temp_focus’ generic function to normalise time intervals using the FOCUS method, with methods for numeric vectors and ‘mkindsg’ objects

      • +

    • ‘mkindsg’ R6 class for groups of ‘mkinds’ datasets with metadata

      • +

    • ‘D24_2014’ dataset

      • +

    • ‘focus_soil_moisture’ FOCUS default soil moisture data

    • ‘plot.mixed.mmkin’ method used for ‘nlme.mmkin’ and ‘saem.mmkin’, both inheriting from ‘mixed.mmkin’ (currently virtual)

    • ‘saem’ generic function to fit saemix models, with a generator ‘saem.mmkin’, summary and plot methods

    • ‘transform_odeparms’, ‘backtransform_odeparms’: Use logit transformation for solitary fractions like the g parameter of the DFOP model, or formation fractions for a pathway to only one target variable

      • @@ -478,7 +482,7 @@

      • Add plots to compiled_models vignette

      • Give an explanatory error message when mkinmod fails due to a missing definition of a target variable

        • -

      • print.mkinmod(): Improve formatting when printing mkinmod model definitions

        • +

      • print.mkinmod(): Improve formatting when printing mkinmod model definitions

    @@ -630,7 +634,7 @@

    New features

      -

    • Add the convenience function mkinsub() for creating the lists used in mkinmod()

      • +

    • Add the convenience function mkinsub() for creating the lists used in mkinmod()

    • Add the possibility to fit indeterminate order rate equation (IORE) models using an analytical solution (parent only) or a numeric solution. Paths from IORE compounds to metabolites are supported when using formation fractions (use_of_ff = ‘max’). Note that the numerical solution (method.ode = ‘deSolve’) of the IORE differential equations sometimes fails due to numerical problems.

    • Switch to using the Port algorithm (using a model/trust region approach) per default. While needing more iterations than the Levenberg-Marquardt algorithm previously used per default, it is less sensitive to starting parameters.

    diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml index 438c79b7..bad008d6 100644 --- a/docs/dev/pkgdown.yml +++ b/docs/dev/pkgdown.yml @@ -10,7 +10,7 @@ articles: web_only/NAFTA_examples: NAFTA_examples.html web_only/benchmarks: benchmarks.html web_only/compiled_models: compiled_models.html -last_built: 2020-11-11T18:47Z +last_built: 2020-11-19T14:38Z urls: reference: https://pkgdown.jrwb.de/mkin/reference article: https://pkgdown.jrwb.de/mkin/articles diff --git a/docs/dev/reference/AIC.mmkin.html b/docs/dev/reference/AIC.mmkin.html index a1418b82..b332257e 100644 --- a/docs/dev/reference/AIC.mmkin.html +++ b/docs/dev/reference/AIC.mmkin.html @@ -73,7 +73,7 @@ same dataset." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ same dataset." />
  • - + @@ -140,7 +140,7 @@ same dataset." />

    Calculate the AIC for a column of an mmkin object

    - Source: R/AIC.mmkin.R + Source: R/AIC.mmkin.R
    @@ -150,10 +150,10 @@ same dataset.

    # S3 method for mmkin
-AIC(object, ..., k = 2)
+AIC(object, ..., k = 2)
 
 # S3 method for mmkin
-BIC(object, ...)
    +BIC(object, ...)

    Arguments

    @@ -177,34 +177,45 @@ column.

    As in the generic method (a numeric value for single fits, or a dataframe if there are several fits in the column).

    +

    Author

    + +

    Johannes Ranke

    Examples

    
    # skip, as it takes > 10 s on winbuilder
-  f <- mmkin(c("SFO", "FOMC", "DFOP"),
-    list("FOCUS A" = FOCUS_2006_A,
-         "FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
    #> Warning: Optimisation did not converge:
+  f <- mmkin(c("SFO", "FOMC", "DFOP"),
+    list("FOCUS A" = FOCUS_2006_A,
+         "FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
+
    #> Warning: Optimisation did not converge:
 #> false convergence (8)
      # We get a warning because the FOMC model does not converge for the
   # FOCUS A dataset, as it is well described by SFO
 
-  AIC(f["SFO", "FOCUS A"]) # We get a single number for a single fit
    #> [1] 55.28197
      AIC(f[["SFO", "FOCUS A"]]) # or when extracting an mkinfit object
    #> [1] 55.28197
    
+  AIC(f["SFO", "FOCUS A"]) # We get a single number for a single fit
+
    #> [1] 55.28197
      AIC(f[["SFO", "FOCUS A"]]) # or when extracting an mkinfit object
+
    #> [1] 55.28197
    
   # For FOCUS A, the models fit almost equally well, so the higher the number
   # of parameters, the higher (worse) the AIC
-  AIC(f[, "FOCUS A"])
    #>      df      AIC
+  AIC(f[, "FOCUS A"])
+
    #>      df      AIC
 #> SFO   3 55.28197
 #> FOMC  4 57.28211
-#> DFOP  5 59.28197
      AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
    #>      df      AIC
+#> DFOP  5 59.28197
      AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
+
    #>      df      AIC
 #> SFO   3 49.28197
 #> FOMC  4 49.28211
-#> DFOP  5 49.28197
      BIC(f[, "FOCUS A"])        # Comparing the BIC gives a very similar picture
    #>      df      BIC
+#> DFOP  5 49.28197
      BIC(f[, "FOCUS A"])        # Comparing the BIC gives a very similar picture
+
    #>      df      BIC
 #> SFO   3 55.52030
 #> FOMC  4 57.59987
 #> DFOP  5 59.67918
    
   # For FOCUS C, the more complex models fit better
-  AIC(f[, "FOCUS C"])
    #>      df      AIC
+  AIC(f[, "FOCUS C"])
+
    #>      df      AIC
 #> SFO   3 59.29336
 #> FOMC  4 44.68652
-#> DFOP  5 29.02372
      BIC(f[, "FOCUS C"])
    #>      df      BIC
+#> DFOP  5 29.02372
      BIC(f[, "FOCUS C"])
+
    #>      df      BIC
 #> SFO   3 59.88504
 #> FOMC  4 45.47542
 #> DFOP  5 30.00984
      
@@ -225,7 +236,7 @@ dataframe if there are several fits in the column).
    
 
    
 
 
    
-  
    Site built with pkgdown 1.5.1.
    
+  
    Site built with pkgdown 1.6.1.
    
 
    
 
       
diff --git a/docs/dev/reference/D24_2014.html b/docs/dev/reference/D24_2014.html
new file mode 100644
index 00000000..ba768186
--- /dev/null
+++ b/docs/dev/reference/D24_2014.html
@@ -0,0 +1,251 @@
+
+
+
+  
+  
+
+
+
+Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 — D24_2014 • mkin
+
+
+
+
+
+
+
+
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+
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+
+
+
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+
+
+
+
+
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+
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+
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+  
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+  
+    
    
+      
    
+      
+
+      
+
+      
    
+
+
    
+  
    
+    
    
+    
    Aerobic soil degradation data on 2,4-D from the EU assessment in 2014
    
+    Source: R/D24_2014.R
+    
+    
    
+
+    
    
+    
    The five datasets were extracted from the active substance evaluation dossier
+published by EFSA. Kinetic evaluations shown for these datasets are intended
+to illustrate and advance kinetic modelling. The fact that these data and
+some results are shown here does not imply a license to use them in the
+context of pesticide  registrations, as the use of the data may be
+constrained by data protection regulations.
    
+    
    
+
+    
    D24_2014
    
+
+
+    
    Format
    
+
+    
    An mkindsg object grouping five datasets
    
+    
    Source
    
+
+    
    Hellenic Ministry of Rural Development and Agriculture (2014)
+Final addendum to the Renewal Assessment Report - public version - 2,4-D
+Volume 3 Annex B.8 Fate and behaviour in the environment
+http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-3812
    
+    
    Details
    
+
+    
    Data for the first dataset are from p. 685. Data for the other four
+datasets were used in the preprocessed versions given in the kinetics
+section (p. 761ff.), with the exception of residues smaller than 1 for DCP
+in the soil from Site I2, where the values given on p. 694 were used.
    
+
    The R code used to create this data object is installed with this package
+in the 'dataset_generation' directory. In the code, page numbers are given for
+specific pieces of information in the comments.
    
+
+    
    Examples
    
+    
    print(D24_2014)
+
    #> <mkindsg> holding 5 mkinds objects
+#> Title $title:  Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 
+#> Occurrene of observed compounds $observed_n:
+#> D24 DCP DCA 
+#>   5   4   4 
+#> Meta information $meta:
+#>                       study usda_soil_type study_moisture_ref_type rel_moisture
+#> 1                Cohen 1991      Silt loam                    <NA>           NA
+#> 2 Liu and Adelfinskaya 2011      Silt loam                     pF1          0.5
+#> 3 Liu and Adelfinskaya 2011           Loam                     pF1          0.5
+#> 4 Liu and Adelfinskaya 2011           Loam                     pF1          0.5
+#> 5 Liu and Adelfinskaya 2011     Loamy sand                     pF1          0.5
+#>   temperature
+#> 1          25
+#> 2          20
+#> 3          20
+#> 4          20
+#> 5          20
    print(D24_2014$ds[[1]], data = TRUE)
+
    #> <mkinds> with $title:  Mississippi 
+#> Observed compounds $observed:  D24 
+#> Sampling times $sampling_times:
+#> 0, 2, 4, 7, 15, 24, 35, 56, 71, 114, 183, 273, 365 
+#> With a maximum of  1  replicates
+#>    time  D24
+#> 1     0 96.8
+#> 2     2 81.0
+#> 3     4 81.7
+#> 4     7 88.2
+#> 5    15 66.3
+#> 6    24 72.9
+#> 7    35 62.6
+#> 8    56 54.6
+#> 9    71 35.2
+#> 10  114 18.0
+#> 11  183 11.3
+#> 12  273  9.9
+#> 13  365  6.3
    m_D24 = mkinmod(D24 = mkinsub("SFO", to = "DCP"),
+  DCP = mkinsub("SFO", to = "DCA"),
+  DCA = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
+  
    
+  
+
    
+
+
+      
    
+      
    
+  
    Developed by Johannes Ranke.
    
+
    
+
+
    
+  
    Site built with pkgdown 1.6.1.
    
+
    
+
+      
    
+   
    
+
+  
+
+
+  
+
+
+
diff --git a/docs/dev/reference/DFOP.solution-1.png b/docs/dev/reference/DFOP.solution-1.png
index a2d75ccc..616e19d5 100644
Binary files a/docs/dev/reference/DFOP.solution-1.png and b/docs/dev/reference/DFOP.solution-1.png differ
diff --git a/docs/dev/reference/DFOP.solution.html b/docs/dev/reference/DFOP.solution.html
index e7c69fc3..22b28732 100644
--- a/docs/dev/reference/DFOP.solution.html
+++ b/docs/dev/reference/DFOP.solution.html
@@ -73,7 +73,7 @@ two exponential decline functions." />
       
       
         mkin
-        0.9.50.3
+        0.9.50.4
       
     
 
@@ -121,7 +121,7 @@ two exponential decline functions." />
       
       
      
         
    • 
-  
+  
     
      
   
@@ -140,7 +140,7 @@ two exponential decline functions." />
   
      
     
      
     
      Double First-Order in Parallel kinetics
      
-    Source: R/parent_solutions.R
+    Source: R/parent_solutions.R
     
     
      
 
@@ -149,7 +149,7 @@ two exponential decline functions." />
 two exponential decline functions.
      
     
      
 
-    
      DFOP.solution(t, parent_0, k1, k2, g)
      
+    
      DFOP.solution(t, parent_0, k1, k2, g)
      
 
     
      Arguments
    @@ -204,7 +204,8 @@ Version 1.1, 18 December 2014

    Examples

    
-  plot(function(x) DFOP.solution(x, 100, 5, 0.5, 0.3), 0, 4, ylim = c(0,100))
    
+  plot(function(x) DFOP.solution(x, 100, 5, 0.5, 0.3), 0, 4, ylim = c(0,100))
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/FOMC.solution-1.png b/docs/dev/reference/FOMC.solution-1.png index aa41a253..1d32355a 100644 Binary files a/docs/dev/reference/FOMC.solution-1.png and b/docs/dev/reference/FOMC.solution-1.png differ diff --git a/docs/dev/reference/FOMC.solution.html b/docs/dev/reference/FOMC.solution.html index f89f87c9..ed5c4d21 100644 --- a/docs/dev/reference/FOMC.solution.html +++ b/docs/dev/reference/FOMC.solution.html @@ -73,7 +73,7 @@ a decreasing rate constant." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ a decreasing rate constant." />
    • - + @@ -140,7 +140,7 @@ a decreasing rate constant." />

      First-Order Multi-Compartment kinetics

      - Source: R/parent_solutions.R + Source: R/parent_solutions.R
      @@ -149,7 +149,7 @@ a decreasing rate constant." /> a decreasing rate constant.

      - 
      FOMC.solution(t, parent_0, alpha, beta)
      + 
      FOMC.solution(t, parent_0, alpha, beta)

      Arguments

    @@ -213,7 +213,8 @@ Technology24, 1032-1038

    Examples

    
-  plot(function(x) FOMC.solution(x, 100, 10, 2), 0, 2, ylim = c(0, 100))
    
+  plot(function(x) FOMC.solution(x, 100, 10, 2), 0, 2, ylim = c(0, 100))
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/HS.solution-1.png b/docs/dev/reference/HS.solution-1.png index ae056d9b..32d04b2d 100644 Binary files a/docs/dev/reference/HS.solution-1.png and b/docs/dev/reference/HS.solution-1.png differ diff --git a/docs/dev/reference/HS.solution.html b/docs/dev/reference/HS.solution.html index 4622ac80..8cf5c7f9 100644 --- a/docs/dev/reference/HS.solution.html +++ b/docs/dev/reference/HS.solution.html @@ -73,7 +73,7 @@ between them." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ between them." />
    • - + @@ -140,7 +140,7 @@ between them." />

      Hockey-Stick kinetics

      - Source: R/parent_solutions.R + Source: R/parent_solutions.R
      @@ -149,7 +149,7 @@ between them." /> between them.

      - 
      HS.solution(t, parent_0, k1, k2, tb)
      + 
      HS.solution(t, parent_0, k1, k2, tb)

      Arguments

    @@ -205,7 +205,8 @@ Version 1.1, 18 December 2014

    Examples

    
-  plot(function(x) HS.solution(x, 100, 2, 0.3, 0.5), 0, 2, ylim=c(0,100))
    
+  plot(function(x) HS.solution(x, 100, 2, 0.3, 0.5), 0, 2, ylim=c(0,100))
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/IORE.solution-1.png b/docs/dev/reference/IORE.solution-1.png index 00e28460..42643a58 100644 Binary files a/docs/dev/reference/IORE.solution-1.png and b/docs/dev/reference/IORE.solution-1.png differ diff --git a/docs/dev/reference/IORE.solution.html b/docs/dev/reference/IORE.solution.html index 26a34c73..29d615dc 100644 --- a/docs/dev/reference/IORE.solution.html +++ b/docs/dev/reference/IORE.solution.html @@ -73,7 +73,7 @@ a concentration dependent rate constant." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ a concentration dependent rate constant." />
    • - + @@ -140,7 +140,7 @@ a concentration dependent rate constant." />

      Indeterminate order rate equation kinetics

      - Source: R/parent_solutions.R + Source: R/parent_solutions.R
      @@ -149,7 +149,7 @@ a concentration dependent rate constant." /> a concentration dependent rate constant.

      - 
      IORE.solution(t, parent_0, k__iore, N)
      + 
      IORE.solution(t, parent_0, k__iore, N)

      Arguments

    @@ -198,21 +198,24 @@ for Evaluating and Calculating Degradation Kinetics in Environmental Media

    Examples

    
-  plot(function(x) IORE.solution(x, 100, 0.2, 1.3), 0, 2, ylim = c(0, 100))
      # \dontrun{
-    fit.fomc <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-    fit.iore <- mkinfit("IORE", FOCUS_2006_C, quiet = TRUE)
-    fit.iore.deS <- mkinfit("IORE", FOCUS_2006_C, solution_type = "deSolve", quiet = TRUE)
-
-    print(data.frame(fit.fomc$par, fit.iore$par, fit.iore.deS$par,
-                     row.names = paste("model par", 1:4)))
    #>             fit.fomc.par fit.iore.par fit.iore.deS.par
+  plot(function(x) IORE.solution(x, 100, 0.2, 1.3), 0, 2, ylim = c(0, 100))
+
      # \dontrun{
+    fit.fomc <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+    fit.iore <- mkinfit("IORE", FOCUS_2006_C, quiet = TRUE)
+    fit.iore.deS <- mkinfit("IORE", FOCUS_2006_C, solution_type = "deSolve", quiet = TRUE)
+
+    print(data.frame(fit.fomc$par, fit.iore$par, fit.iore.deS$par, 
+                     row.names = paste("model par", 1:4)))
+
    #>             fit.fomc.par fit.iore.par fit.iore.deS.par
 #> model par 1  85.87489063    85.874890        85.874890
 #> model par 2   0.05192238    -4.826631        -4.826631
 #> model par 3   0.65096665     1.949403         1.949403
-#> model par 4   1.85744396     1.857444         1.857444
        print(rbind(fomc = endpoints(fit.fomc)$distimes, iore = endpoints(fit.iore)$distimes,
-                iore.deS = endpoints(fit.iore)$distimes))
    #>              DT50    DT90 DT50back
+#> model par 4   1.85744396     1.857444         1.857444
        print(rbind(fomc = endpoints(fit.fomc)$distimes, iore = endpoints(fit.iore)$distimes, 
+                iore.deS = endpoints(fit.iore)$distimes))
+
    #>              DT50    DT90 DT50back
 #> fomc     1.785233 15.1479 4.559973
 #> iore     1.785233 15.1479 4.559973
-#> iore.deS 1.785233 15.1479 4.559973
      # }
+#> iore.deS 1.785233 15.1479 4.559973
      # }
    @@ -230,7 +233,7 @@ for Evaluating and Calculating Degradation Kinetics in Environmental Media

    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png index 17a35806..f001da49 100644 Binary files a/docs/dev/reference/Rplot001.png and b/docs/dev/reference/Rplot001.png differ diff --git a/docs/dev/reference/Rplot002.png b/docs/dev/reference/Rplot002.png index 9b97a634..c6c75f42 100644 Binary files a/docs/dev/reference/Rplot002.png and b/docs/dev/reference/Rplot002.png differ diff --git a/docs/dev/reference/Rplot003.png b/docs/dev/reference/Rplot003.png index ff6bc722..41711ba6 100644 Binary files a/docs/dev/reference/Rplot003.png and b/docs/dev/reference/Rplot003.png differ diff --git a/docs/dev/reference/Rplot004.png b/docs/dev/reference/Rplot004.png index 98dd019e..875d6daf 100644 Binary files a/docs/dev/reference/Rplot004.png and b/docs/dev/reference/Rplot004.png differ diff --git a/docs/dev/reference/Rplot005.png b/docs/dev/reference/Rplot005.png index 5e675828..91c7777b 100644 Binary files a/docs/dev/reference/Rplot005.png and b/docs/dev/reference/Rplot005.png differ diff --git a/docs/dev/reference/Rplot006.png b/docs/dev/reference/Rplot006.png index 511c6b00..921e0394 100644 Binary files a/docs/dev/reference/Rplot006.png and b/docs/dev/reference/Rplot006.png differ diff --git a/docs/dev/reference/Rplot007.png b/docs/dev/reference/Rplot007.png index a0d6336e..fcca232c 100644 Binary files a/docs/dev/reference/Rplot007.png and b/docs/dev/reference/Rplot007.png differ diff --git a/docs/dev/reference/SFO.solution-1.png b/docs/dev/reference/SFO.solution-1.png index b0b854bb..56d27ef6 100644 Binary files a/docs/dev/reference/SFO.solution-1.png and b/docs/dev/reference/SFO.solution-1.png differ diff --git a/docs/dev/reference/SFO.solution.html b/docs/dev/reference/SFO.solution.html index 930c2a97..b3e7ef9a 100644 --- a/docs/dev/reference/SFO.solution.html +++ b/docs/dev/reference/SFO.solution.html @@ -72,7 +72,7 @@ mkin - 0.9.50.3 + 0.9.50.4 @@ -120,7 +120,7 @@
    • - + @@ -139,7 +139,7 @@

      Single First-Order kinetics

      - Source: R/parent_solutions.R + Source: R/parent_solutions.R
      @@ -147,7 +147,7 @@

      Function describing exponential decline from a defined starting value.

      - 
      SFO.solution(t, parent_0, k)
      + 
      SFO.solution(t, parent_0, k)

      Arguments

    @@ -193,7 +193,8 @@ Version 1.1, 18 December 2014

    Examples

    
-  plot(function(x) SFO.solution(x, 100, 3), 0, 2)
    
+  plot(function(x) SFO.solution(x, 100, 3), 0, 2)
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/SFORB.solution-1.png b/docs/dev/reference/SFORB.solution-1.png index cd58caec..4eeb0d41 100644 Binary files a/docs/dev/reference/SFORB.solution-1.png and b/docs/dev/reference/SFORB.solution-1.png differ diff --git a/docs/dev/reference/SFORB.solution.html b/docs/dev/reference/SFORB.solution.html index 845377a2..9310212f 100644 --- a/docs/dev/reference/SFORB.solution.html +++ b/docs/dev/reference/SFORB.solution.html @@ -76,7 +76,7 @@ and no substance in the bound fraction." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -124,7 +124,7 @@ and no substance in the bound fraction." />
    • - + @@ -143,7 +143,7 @@ and no substance in the bound fraction." />

      Single First-Order Reversible Binding kinetics

      - Source: R/parent_solutions.R + Source: R/parent_solutions.R
      @@ -155,7 +155,7 @@ fraction. The initial condition is a defined amount in the free fraction and no substance in the bound fraction.

      - 
      SFORB.solution(t, parent_0, k_12, k_21, k_1output)
      + 
      SFORB.solution(t, parent_0, k_12, k_21, k_1output)

      Arguments

    @@ -211,7 +211,8 @@ Version 1.1, 18 December 2014

    Examples

    
-  plot(function(x) SFORB.solution(x, 100, 0.5, 2, 3), 0, 2)
    
+  plot(function(x) SFORB.solution(x, 100, 0.5, 2, 3), 0, 2)
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/add_err-1.png b/docs/dev/reference/add_err-1.png index f5686754..d2ce797f 100644 Binary files a/docs/dev/reference/add_err-1.png and b/docs/dev/reference/add_err-1.png differ diff --git a/docs/dev/reference/add_err.html b/docs/dev/reference/add_err.html index e362ab7a..ae10e863 100644 --- a/docs/dev/reference/add_err.html +++ b/docs/dev/reference/add_err.html @@ -222,8 +222,8 @@ https://jrwb.de/posters/piacenza_2015.pdf

    Examples

    
 # The kinetic model
-m_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
-                     M1 = mkinsub("SFO"), use_of_ff = "max")
+m_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
+                     M1 = mkinsub("SFO"), use_of_ff = "max")
 
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # Generate a prediction for a specific set of parameters
 sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
diff --git a/docs/dev/reference/confint.mkinfit.html b/docs/dev/reference/confint.mkinfit.html
index 5b683355..745f2dc4 100644
--- a/docs/dev/reference/confint.mkinfit.html
+++ b/docs/dev/reference/confint.mkinfit.html
@@ -79,7 +79,7 @@ method of Venzon and Moolgavkar (1988)." />
       
       
         mkin
-        0.9.50.3
+        0.9.50.4
       
     
    
 
@@ -127,7 +127,7 @@ method of Venzon and Moolgavkar (1988)." />
       
       
      
         
    • 
-  
+  
     
      
   
@@ -146,7 +146,7 @@ method of Venzon and Moolgavkar (1988)." />
   
      
     
      
     
      Confidence intervals for parameters of mkinfit objects
      
-    Source: R/confint.mkinfit.R
+    Source: R/confint.mkinfit.R
     
     
      
 
@@ -162,20 +162,20 @@ method of Venzon and Moolgavkar (1988).
      
     
      
 
     
      # S3 method for mkinfit
-confint(
-  object,
-  parm,
-  level = 0.95,
-  alpha = 1 - level,
-  cutoff,
-  method = c("quadratic", "profile"),
-  transformed = TRUE,
-  backtransform = TRUE,
-  cores = parallel::detectCores(),
-  rel_tol = 0.01,
-  quiet = FALSE,
-  ...
-)
      
+confint(
+  object,
+  parm,
+  level = 0.95,
+  alpha = 1 - level,
+  cutoff,
+  method = c("quadratic", "profile"),
+  transformed = TRUE,
+  backtransform = TRUE,
+  cores = parallel::detectCores(),
+  rel_tol = 0.01,
+  quiet = FALSE,
+  ...
+)

    Arguments

    @@ -257,68 +257,79 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, 87–94.

    Examples

    - 
    f <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
-confint(f, method = "quadratic")
    #>                2.5%      97.5%
+    
    f <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
+confint(f, method = "quadratic")
+
    #>                2.5%      97.5%
 #> parent_0 71.8242430 93.1600766
 #> k_parent  0.2109541  0.4440528
 #> sigma     1.9778868  7.3681380
    
 # \dontrun{
-confint(f, method = "profile")
    #> Profiling the likelihood
    #>                2.5%      97.5%
+confint(f, method = "profile")
+
    #> Profiling the likelihood
    #>                2.5%      97.5%
 #> parent_0 73.0641834 92.1392181
 #> k_parent  0.2170293  0.4235348
 #> sigma     3.1307772  8.0628314
    
 # Set the number of cores for the profiling method for further examples
-if (identical(Sys.getenv("NOT_CRAN"), "true")) {
-  n_cores <- parallel::detectCores() - 1
-} else {
- n_cores <- 1
-}
-if (Sys.getenv("TRAVIS") != "") n_cores = 1
-if (Sys.info()["sysname"] == "Windows") n_cores = 1
-
-SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), quiet = TRUE)
-SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"),
-  use_of_ff = "max", quiet = TRUE)
-f_d_1 <- mkinfit(SFO_SFO, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    system.time(ci_profile <- confint(f_d_1, method = "profile", cores = 1, quiet = TRUE))
    #>    user  system elapsed 
-#>   3.810   0.964   3.430 
    # Using more cores does not save much time here, as parent_0 takes up most of the time
+if (identical(Sys.getenv("NOT_CRAN"), "true")) {
+  n_cores <- parallel::detectCores() - 1
+} else {
+ n_cores <- 1
+}
+if (Sys.getenv("TRAVIS") != "") n_cores = 1
+if (Sys.info()["sysname"] == "Windows") n_cores = 1
+
+SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), quiet = TRUE)
+SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"),
+  use_of_ff = "max", quiet = TRUE)
+f_d_1 <- mkinfit(SFO_SFO, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
+system.time(ci_profile <- confint(f_d_1, method = "profile", cores = 1, quiet = TRUE))
+
    #>    user  system elapsed 
+#>   3.829   1.000   3.519 
    # Using more cores does not save much time here, as parent_0 takes up most of the time
 # If we additionally exclude parent_0 (the confidence of which is often of
 # minor interest), we get a nice performance improvement from about 50
 # seconds to about 12 seconds if we use at least four cores
-system.time(ci_profile_no_parent_0 <- confint(f_d_1, method = "profile",
-  c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = n_cores))
    #> Profiling the likelihood
    #> Warning: scheduled cores 2, 1, 3 encountered errors in user code, all values of the jobs will be affected
    #> Error in dimnames(x) <- dn: length of 'dimnames' [2] not equal to array extent
    #> Timing stopped at: 0.015 0.029 0.198
    ci_profile
    #>                        2.5%        97.5%
+system.time(ci_profile_no_parent_0 <- confint(f_d_1, method = "profile",
+  c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = n_cores))
+
    #> Profiling the likelihood
    #> Warning: scheduled cores 2, 1, 3 encountered errors in user code, all values of the jobs will be affected
    #> Error in dimnames(x) <- dn: length of 'dimnames' [2] not equal to array extent
    #> Timing stopped at: 0.011 0.029 0.241
    ci_profile
+
    #>                        2.5%        97.5%
 #> parent_0       96.456003640 1.027703e+02
 #> k_parent        0.090911032 1.071578e-01
-#> k_m1            0.003892605 6.702778e-03
+#> k_m1            0.003892606 6.702775e-03
 #> f_parent_to_m1  0.471328495 5.611550e-01
-#> sigma           2.535612399 3.985263e+00
    ci_quadratic_transformed <- confint(f_d_1, method = "quadratic")
-ci_quadratic_transformed
    #>                        2.5%        97.5%
-#> parent_0       96.403839460 1.027931e+02
-#> k_parent        0.090823790 1.072543e-01
-#> k_m1            0.004012216 6.897547e-03
-#> f_parent_to_m1  0.469118713 5.595960e-01
-#> sigma           2.396089689 3.854918e+00
    ci_quadratic_untransformed <- confint(f_d_1, method = "quadratic", transformed = FALSE)
-ci_quadratic_untransformed
    #>                        2.5%        97.5%
-#> parent_0       96.403839413 1.027931e+02
-#> k_parent        0.090491931 1.069035e-01
-#> k_m1            0.003835483 6.685819e-03
-#> f_parent_to_m1  0.469113365 5.598386e-01
+#> sigma           2.535612399 3.985263e+00
    ci_quadratic_transformed <- confint(f_d_1, method = "quadratic")
+ci_quadratic_transformed
+
    #>                        2.5%        97.5%
+#> parent_0       96.403833585 102.79311650
+#> k_parent        0.090823771   0.10725430
+#> k_m1            0.004012219   0.00689755
+#> f_parent_to_m1  0.469118824   0.55959615
+#> sigma           2.396089689   3.85491806
    ci_quadratic_untransformed <- confint(f_d_1, method = "quadratic", transformed = FALSE)
+ci_quadratic_untransformed
+
    #>                        2.5%        97.5%
+#> parent_0       96.403833589 1.027931e+02
+#> k_parent        0.090491913 1.069035e-01
+#> k_m1            0.003835485 6.685823e-03
+#> f_parent_to_m1  0.469113477 5.598387e-01
 #> sigma           2.396089689 3.854918e+00
    # Against the expectation based on Bates and Watts (1988), the confidence
 # intervals based on the internal parameter transformation are less
 # congruent with the likelihood based intervals. Note the superiority of the
 # interval based on the untransformed fit for k_m1_sink
-rel_diffs_transformed <- abs((ci_quadratic_transformed - ci_profile)/ci_profile)
-rel_diffs_untransformed <- abs((ci_quadratic_untransformed - ci_profile)/ci_profile)
-rel_diffs_transformed < rel_diffs_untransformed
    #>                 2.5% 97.5%
-#> parent_0        TRUE  TRUE
+rel_diffs_transformed <- abs((ci_quadratic_transformed - ci_profile)/ci_profile)
+rel_diffs_untransformed <- abs((ci_quadratic_untransformed - ci_profile)/ci_profile)
+rel_diffs_transformed < rel_diffs_untransformed
+
    #>                 2.5% 97.5%
+#> parent_0       FALSE FALSE
 #> k_parent        TRUE  TRUE
 #> k_m1           FALSE FALSE
 #> f_parent_to_m1  TRUE FALSE
-#> sigma          FALSE FALSE
    signif(rel_diffs_transformed, 3)
    #>                    2.5%    97.5%
+#> sigma           TRUE FALSE
    signif(rel_diffs_transformed, 3)
+
    #>                    2.5%    97.5%
 #> parent_0       0.000541 0.000222
 #> k_parent       0.000960 0.000900
 #> k_m1           0.030700 0.029100
 #> f_parent_to_m1 0.004690 0.002780
-#> sigma          0.055000 0.032700
    signif(rel_diffs_untransformed, 3)
    #>                    2.5%    97.5%
+#> sigma          0.055000 0.032700
    signif(rel_diffs_untransformed, 3)
+
    #>                    2.5%    97.5%
 #> parent_0       0.000541 0.000222
 #> k_parent       0.004610 0.002370
 #> k_m1           0.014700 0.002530
@@ -326,66 +337,76 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,
 #> sigma          0.055000 0.032700
    
 
 # Investigate a case with formation fractions
-f_d_2 <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    ci_profile_ff <- confint(f_d_2, method = "profile", cores = n_cores)
    #> Profiling the likelihood
    ci_profile_ff
    #>                        2.5%        97.5%
+f_d_2 <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
+ci_profile_ff <- confint(f_d_2, method = "profile", cores = n_cores)
+
    #> Profiling the likelihood
    ci_profile_ff
+
    #>                        2.5%        97.5%
 #> parent_0       96.456003640 1.027703e+02
 #> k_parent        0.090911032 1.071578e-01
-#> k_m1            0.003892605 6.702778e-03
+#> k_m1            0.003892606 6.702775e-03
 #> f_parent_to_m1  0.471328495 5.611550e-01
-#> sigma           2.535612399 3.985263e+00
    ci_quadratic_transformed_ff <- confint(f_d_2, method = "quadratic")
-ci_quadratic_transformed_ff
    #>                        2.5%        97.5%
-#> parent_0       96.403839460 1.027931e+02
-#> k_parent        0.090823790 1.072543e-01
-#> k_m1            0.004012216 6.897547e-03
-#> f_parent_to_m1  0.469118713 5.595960e-01
-#> sigma           2.396089689 3.854918e+00
    ci_quadratic_untransformed_ff <- confint(f_d_2, method = "quadratic", transformed = FALSE)
-ci_quadratic_untransformed_ff
    #>                        2.5%        97.5%
-#> parent_0       96.403839413 1.027931e+02
-#> k_parent        0.090491931 1.069035e-01
-#> k_m1            0.003835483 6.685819e-03
-#> f_parent_to_m1  0.469113365 5.598386e-01
-#> sigma           2.396089689 3.854918e+00
    rel_diffs_transformed_ff <- abs((ci_quadratic_transformed_ff - ci_profile_ff)/ci_profile_ff)
-rel_diffs_untransformed_ff <- abs((ci_quadratic_untransformed_ff - ci_profile_ff)/ci_profile_ff)
+#> sigma           2.535612399 3.985263e+00
    ci_quadratic_transformed_ff <- confint(f_d_2, method = "quadratic")
+ci_quadratic_transformed_ff
+
    #>                        2.5%        97.5%
+#> parent_0       96.403833585 102.79311650
+#> k_parent        0.090823771   0.10725430
+#> k_m1            0.004012219   0.00689755
+#> f_parent_to_m1  0.469118824   0.55959615
+#> sigma           2.396089689   3.85491806
    ci_quadratic_untransformed_ff <- confint(f_d_2, method = "quadratic", transformed = FALSE)
+ci_quadratic_untransformed_ff
+
    #>                        2.5%        97.5%
+#> parent_0       96.403833589 1.027931e+02
+#> k_parent        0.090491913 1.069035e-01
+#> k_m1            0.003835485 6.685823e-03
+#> f_parent_to_m1  0.469113477 5.598387e-01
+#> sigma           2.396089689 3.854918e+00
    rel_diffs_transformed_ff <- abs((ci_quadratic_transformed_ff - ci_profile_ff)/ci_profile_ff)
+rel_diffs_untransformed_ff <- abs((ci_quadratic_untransformed_ff - ci_profile_ff)/ci_profile_ff)
 # While the confidence interval for the parent rate constant is closer to
 # the profile based interval when using the internal parameter
 # transformation, the interval for the metabolite rate constant is 'better
 # without internal parameter transformation.
-rel_diffs_transformed_ff < rel_diffs_untransformed_ff
    #>                 2.5% 97.5%
-#> parent_0        TRUE  TRUE
+rel_diffs_transformed_ff < rel_diffs_untransformed_ff
+
    #>                 2.5% 97.5%
+#> parent_0       FALSE FALSE
 #> k_parent        TRUE  TRUE
 #> k_m1           FALSE FALSE
 #> f_parent_to_m1  TRUE FALSE
-#> sigma          FALSE FALSE
    rel_diffs_transformed_ff
    #>                        2.5%        97.5%
-#> parent_0       0.0005408080 0.0002217794
-#> k_parent       0.0009596417 0.0009003876
-#> k_m1           0.0307277370 0.0290579182
-#> f_parent_to_m1 0.0046884130 0.0027782556
-#> sigma          0.0550252516 0.0327066836
    rel_diffs_untransformed_ff
    #>                        2.5%        97.5%
-#> parent_0       0.0005408085 0.0002217799
-#> k_parent       0.0046100096 0.0023730229
-#> k_m1           0.0146746469 0.0025301011
-#> f_parent_to_m1 0.0046997599 0.0023460223
+#> sigma           TRUE FALSE
    rel_diffs_transformed_ff
+
    #>                        2.5%        97.5%
+#> parent_0       0.0005408689 0.0002217234
+#> k_parent       0.0009598532 0.0009001864
+#> k_m1           0.0307283044 0.0290588365
+#> f_parent_to_m1 0.0046881768 0.0027780063
+#> sigma          0.0550252516 0.0327066836
    rel_diffs_untransformed_ff
+
    #>                        2.5%        97.5%
+#> parent_0       0.0005408689 0.0002217233
+#> k_parent       0.0046102155 0.0023732281
+#> k_m1           0.0146740688 0.0025291817
+#> f_parent_to_m1 0.0046995211 0.0023457712
 #> sigma          0.0550252516 0.0327066836
    
 # The profiling for the following fit does not finish in a reasonable time,
 # therefore we use the quadratic approximation
-m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
-  M1 = mkinsub("SFO"),
-  M2 = mkinsub("SFO"),
-  use_of_ff = "max", quiet = TRUE)
-DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
-f_tc_2 <- mkinfit(m_synth_DFOP_par, DFOP_par_c, error_model = "tc",
-  error_model_algorithm = "direct", quiet = TRUE)
-confint(f_tc_2, method = "quadratic")
    #>                       2.5%        97.5%
-#> parent_0       94.59613833 106.19939215
-#> k_M1            0.03760542   0.04490759
-#> k_M2            0.00856874   0.01087675
-#> f_parent_to_M1  0.02146166   0.62023888
-#> f_parent_to_M2  0.01516502   0.37975343
-#> k1              0.27389751   0.33388078
-#> k2              0.01861456   0.02250379
-#> g               0.67194349   0.73583256
-#> sigma_low       0.25128383   0.83992146
-#> rsd_high        0.04041100   0.07662001
    confint(f_tc_2, "parent_0", method = "quadratic")
    #>              2.5%    97.5%
-#> parent_0 94.59614 106.1994
    # }
+m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
+  M1 = mkinsub("SFO"),
+  M2 = mkinsub("SFO"),
+  use_of_ff = "max", quiet = TRUE)
+DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
+f_tc_2 <- mkinfit(m_synth_DFOP_par, DFOP_par_c, error_model = "tc",
+  error_model_algorithm = "direct", quiet = TRUE)
+confint(f_tc_2, method = "quadratic")
+
    #>                        2.5%        97.5%
+#> parent_0       94.596126334 106.19944007
+#> k_M1            0.037605408   0.04490759
+#> k_M2            0.008568739   0.01087675
+#> f_parent_to_M1  0.021463787   0.62023881
+#> f_parent_to_M2  0.015166531   0.37975349
+#> k1              0.273897467   0.33388084
+#> k2              0.018614555   0.02250379
+#> g               0.671943606   0.73583278
+#> sigma_low       0.251283766   0.83992113
+#> rsd_high        0.040411014   0.07662005
    confint(f_tc_2, "parent_0", method = "quadratic")
+
    #>              2.5%    97.5%
+#> parent_0 94.59613 106.1994
    # }
 
    
   
    
   
 
 
    
-  
    Site built with pkgdown 1.5.1.
    
+  
    Site built with pkgdown 1.6.1.
    
 
    
 
       
diff --git a/docs/dev/reference/create_deg_func.html b/docs/dev/reference/create_deg_func.html
index a25fa165..9f2e4deb 100644
--- a/docs/dev/reference/create_deg_func.html
+++ b/docs/dev/reference/create_deg_func.html
@@ -72,7 +72,7 @@
       
       
         mkin
-        0.9.50.3
+        0.9.50.4
       
     
 
@@ -120,7 +120,7 @@
       
       
      
         
    • 
-  
+  
     
      
   
@@ -139,7 +139,7 @@
   
      
     
      
     
      Create degradation functions for known analytical solutions
      
-    Source: R/create_deg_func.R
+    Source: R/create_deg_func.R
     
     
      
 
@@ -147,7 +147,7 @@
     
      Create degradation functions for known analytical solutions
      
     
      
 
-    
      create_deg_func(spec, use_of_ff = c("min", "max"))
      
+    
      create_deg_func(spec, use_of_ff = c("min", "max"))
      
 
     
      Arguments
    @@ -168,30 +168,36 @@

    Examples

    
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    FOCUS_D <- subset(FOCUS_2006_D, value != 0) # to avoid warnings
-fit_1 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    fit_2 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    # \dontrun{
-if (require(rbenchmark))
-  benchmark(
-    analytical = mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
-    deSolve = mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE),
-    replications = 2)
    #> Loading required package: rbenchmark
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    #>         test replications elapsed relative user.self sys.self user.child
-#> 1 analytical            2   0.423    1.000     0.423        0          0
-#> 2    deSolve            2   0.716    1.693     0.715        0          0
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    FOCUS_D <- subset(FOCUS_2006_D, value != 0) # to avoid warnings
+fit_1 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE)
+fit_2 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE)
+# \dontrun{
+if (require(rbenchmark))
+  benchmark(
+    analytical = mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
+    deSolve = mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE),
+    replications = 2)
+
    #> Loading required package: rbenchmark
    #>         test replications elapsed relative user.self sys.self user.child
+#> 1 analytical            2   0.397    1.000     0.397    0.001          0
+#> 2    deSolve            2   0.684    1.723     0.683    0.000          0
 #>   sys.child
 #> 1         0
-#> 2         0
      DFOP_SFO <- mkinmod(
-    parent = mkinsub("DFOP", "m1"),
-    m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
      benchmark(
-    analytical = mkinfit(DFOP_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
-    deSolve = mkinfit(DFOP_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE),
-    replications = 2)
    #>         test replications elapsed relative user.self sys.self user.child
-#> 1 analytical            2   0.910    1.000     0.909        0          0
-#> 2    deSolve            2   1.734    1.905     1.733        0          0
+#> 2         0
      DFOP_SFO <- mkinmod(
+    parent = mkinsub("DFOP", "m1"),
+    m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
      benchmark(
+    analytical = mkinfit(DFOP_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
+    deSolve = mkinfit(DFOP_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE),
+    replications = 2)
+
    #>         test replications elapsed relative user.self sys.self user.child
+#> 1 analytical            2   0.834    1.000     0.833    0.001          0
+#> 2    deSolve            2   1.545    1.853     1.541    0.001          0
 #>   sys.child
 #> 1         0
-#> 2         0
    # }
+#> 2         0
    # }
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/experimental_data_for_UBA-1.png b/docs/dev/reference/experimental_data_for_UBA-1.png index b316a5db..24cb54c5 100644 Binary files a/docs/dev/reference/experimental_data_for_UBA-1.png and b/docs/dev/reference/experimental_data_for_UBA-1.png differ diff --git a/docs/dev/reference/experimental_data_for_UBA.html b/docs/dev/reference/experimental_data_for_UBA.html index d49924c7..cd098b7d 100644 --- a/docs/dev/reference/experimental_data_for_UBA.html +++ b/docs/dev/reference/experimental_data_for_UBA.html @@ -60,11 +60,11 @@ Datasets 3 and 4 are from the Renewal Assessment Report (RAR) for isofetamid Dataset 5 is from the Renewal Assessment Report (RAR) for ethofumesate (Austria, 2015, p. 16). Datasets 6 to 10 are from the Renewal Assessment Report (RAR) for glyphosate - (Germany, 2013a, pages 8, 28, 50, 51). For the initial sampling, + (Germany, 2013, pages 8, 28, 50, 51). For the initial sampling, the residues given for the metabolite were added to the parent value, following the recommendation of the FOCUS kinetics workgroup. Dataset 11 is from the Renewal Assessment Report (RAR) for 2,4-D - (Germany, 2013b, p. 644). Values reported as zero were set to NA, with + (Hellas, 2013, p. 644). Values reported as zero were set to NA, with the exception of the day three sampling of metabolite A2, which was set to one half of the LOD reported to be 1% AR. Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl @@ -100,7 +100,7 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl mkin - 0.9.50.3 + 0.9.50.4 @@ -148,7 +148,7 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl
    • - + @@ -192,24 +192,24 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl

      Dataset 5 is from the Renewal Assessment Report (RAR) for ethofumesate (Austria, 2015, p. 16).

      Datasets 6 to 10 are from the Renewal Assessment Report (RAR) for glyphosate - (Germany, 2013a, pages 8, 28, 50, 51). For the initial sampling, + (Germany, 2013, pages 8, 28, 50, 51). For the initial sampling, the residues given for the metabolite were added to the parent value, following the recommendation of the FOCUS kinetics workgroup.

      Dataset 11 is from the Renewal Assessment Report (RAR) for 2,4-D - (Germany, 2013b, p. 644). Values reported as zero were set to NA, with + (Hellas, 2013, p. 644). Values reported as zero were set to NA, with the exception of the day three sampling of metabolite A2, which was set to one half of the LOD reported to be 1% AR.

      Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl (United Kingdom, 2014, p. 81).

      - 
      experimental_data_for_UBA_2019
      + 
      experimental_data_for_UBA_2019

      Format

      A list containing twelve datasets as an R6 class defined by mkinds, - each containing, among others, the following components

      + each containing, among others, the following components

      title

      The name of the dataset, e.g. Soil 1

      data

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

      @@ -227,9 +227,9 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl Registration” Report of the FOCUS Work Group on Degradation Kinetics, Version 1.1, 18 December 2014 http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

      -

      Germany (2013a). Renewal Assessment Report Glyphosate Volume 3 Annex B.8: Environmental Fate +

      Germany (2013). Renewal Assessment Report Glyphosate Volume 3 Annex B.8: Environmental Fate and Behaviour

      -

      Germany (2013b). Renewal Assessment Report 2,4-D Volume 3 Annex B.8: Fate and behaviour in the +

      Hellas (2013). Renewal Assessment Report 2,4-D Volume 3 Annex B.8: Fate and behaviour in the environment

      Ranke (2019) Documentation of results obtained for the error model expertise written for the German Umweltbundesamt.

      @@ -241,35 +241,40 @@ Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl 
      # \dontrun{
 
 # Model definitions
-sfo_sfo <- mkinmod(
-  parent = mkinsub("SFO", to = "A1"),
-  A1 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
      #> Successfully compiled differential equation model from auto-generated C code.
      
-dfop_sfo <- mkinmod(
-  parent = mkinsub("DFOP", to = "A1"),
-  A1 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
      #> Successfully compiled differential equation model from auto-generated C code.
      
-sfo_sfo_sfo <- mkinmod(
-  parent = mkinsub("SFO", to = "A1"),
-  A1 = mkinsub("SFO", to = "A2"),
-  A2 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
      #> Successfully compiled differential equation model from auto-generated C code.
      
-dfop_sfo_sfo <- mkinmod(
-  parent = mkinsub("DFOP", to = "A1"),
-  A1 = mkinsub("SFO", to = "A2"),
-  A2 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
      #> Successfully compiled differential equation model from auto-generated C code.
      d_1_2 <- lapply(experimental_data_for_UBA_2019[1:2], function(x) x$data)
-names(d_1_2) <- paste("Soil", 1:2)
-
-
-f_1_2_tc <- mmkin(list("DFOP-SFO-SFO" = dfop_sfo_sfo), d_1_2, error_model = "tc")
-
-plot(f_1_2_tc, resplot = "errmod")
      
-# }
      +sfo_sfo <- mkinmod( + parent = mkinsub("SFO", to = "A1"), + A1 = mkinsub("SFO"), + use_of_ff = "max" +) +
      #> Successfully compiled differential equation model from auto-generated C code.
      +dfop_sfo <- mkinmod( + parent = mkinsub("DFOP", to = "A1"), + A1 = mkinsub("SFO"), + use_of_ff = "max" +) +
      #> Successfully compiled differential equation model from auto-generated C code.
      +sfo_sfo_sfo <- mkinmod( + parent = mkinsub("SFO", to = "A1"), + A1 = mkinsub("SFO", to = "A2"), + A2 = mkinsub("SFO"), + use_of_ff = "max" +) +
      #> Successfully compiled differential equation model from auto-generated C code.
      +dfop_sfo_sfo <- mkinmod( + parent = mkinsub("DFOP", to = "A1"), + A1 = mkinsub("SFO", to = "A2"), + A2 = mkinsub("SFO"), + use_of_ff = "max" +) +
      #> Successfully compiled differential equation model from auto-generated C code.
      d_1_2 <- lapply(experimental_data_for_UBA_2019[1:2], function(x) x$data) +names(d_1_2) <- paste("Soil", 1:2) + + +f_1_2_tc <- mmkin(list("DFOP-SFO-SFO" = dfop_sfo_sfo), d_1_2, error_model = "tc") + +plot(f_1_2_tc, resplot = "errmod") +
      +# }
      -

      Site built with pkgdown 1.5.1.

      +

      Site built with pkgdown 1.6.1.

      diff --git a/docs/dev/reference/f_time_norm_focus.html b/docs/dev/reference/f_time_norm_focus.html new file mode 100644 index 00000000..a95234a7 --- /dev/null +++ b/docs/dev/reference/f_time_norm_focus.html @@ -0,0 +1,283 @@ + + + + + + + + +Normalisation factors for aerobic soil degradation according to FOCUS guidance — f_time_norm_focus • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
      +
      + + + + +
      + +
      +
      +
      +

      Normalisation factors for aerobic soil degradation according to FOCUS guidance

      + Source: R/f_time_norm_focus.R + +
      + +
      +

      Time step normalisation factors for aerobic soil degradation as described +in Appendix 8 to the FOCUS kinetics guidance (FOCUS 2014, p. 369).

      +
      + + 
      f_time_norm_focus(object, ...)
+
+# S3 method for numeric
+f_time_norm_focus(
+  object,
+  moisture = NA,
+  field_moisture = NA,
+  temperature = object,
+  Q10 = 2.58,
+  walker = 0.7,
+  f_na = NA,
+  ...
+)
+
+# S3 method for mkindsg
+f_time_norm_focus(
+  object,
+  study_moisture_ref_source = c("meta", "focus"),
+  Q10 = 2.58,
+  walker = 0.7,
+  f_na = NA,
+  ...
+)
      + +

      Arguments

      +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    object

    An object containing information used for the calculations

    ...

    Currently not used

    moisture

    Numeric vector of moisture contents in \% w/w

    field_moisture

    Numeric vector of moisture contents at field capacity +(pF2) in \% w/w

    temperature

    Numeric vector of temperatures in °C

    Q10

    The Q10 value used for temperature normalisation

    walker

    The Walker exponent used for moisture normalisation

    f_na

    The factor to use for NA values. If set to NA, only factors +for complete cases will be returned.

    study_moisture_ref_source

    Source for the reference value +used to calculate the study moisture

    + +

    References

    + +

    FOCUS (2006) “Guidance Document on Estimating Persistence +and Degradation Kinetics from Environmental Fate Studies on Pesticides in +EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, +EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, +http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics +FOCUS (2014) “Generic guidance for Estimating Persistence +and Degradation Kinetics from Environmental Fate Studies on Pesticides in +EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, +Version 1.1, 18 December 2014 +http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

    +

    See also

    + +

    focus_soil_moisture

    + +

    Examples

    + 
    f_time_norm_focus(25, 20, 25) # 1.37, compare FOCUS 2014 p. 184
+
    #> [1] 1.373956
    
+D24_2014$meta
+
    #>                       study usda_soil_type study_moisture_ref_type rel_moisture
+#> 1                Cohen 1991      Silt loam                    <NA>           NA
+#> 2 Liu and Adelfinskaya 2011      Silt loam                     pF1          0.5
+#> 3 Liu and Adelfinskaya 2011           Loam                     pF1          0.5
+#> 4 Liu and Adelfinskaya 2011           Loam                     pF1          0.5
+#> 5 Liu and Adelfinskaya 2011     Loamy sand                     pF1          0.5
+#>   temperature
+#> 1          25
+#> 2          20
+#> 3          20
+#> 4          20
+#> 5          20
    # No moisture normalisation in the first dataset, so we use f_na = 1 to get
+# temperature only normalisation as in the EU evaluation
+f_time_norm_focus(D24_2014, study_moisture_ref_source = "focus", f_na = 1)
+
    #> $time_norm was set to
+#> [1] 1.6062378 0.7118732 0.7156063 0.7156063 0.8977124
    #> [1] 1.6062378 0.7118732 0.7156063 0.7156063 0.8977124
    + + + + + +
    +
    +

    Developed by Johannes Ranke.

    +
    + +
    +

    Site built with pkgdown 1.6.1.

    +
    + +
    + + + + + + + + + diff --git a/docs/dev/reference/focus_soil_moisture.html b/docs/dev/reference/focus_soil_moisture.html new file mode 100644 index 00000000..c46fd69a --- /dev/null +++ b/docs/dev/reference/focus_soil_moisture.html @@ -0,0 +1,206 @@ + + + + + + + + +FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar — focus_soil_moisture • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar

    + Source: R/focus_soil_moisture.R + +
    + +
    +

    The value were transcribed from p. 36. The table assumes field capacity +corresponds to pF2, MWHC to pF 1 and 1/3 bar to pF 2.5.

    +
    + + 
    focus_soil_moisture
    + + +

    Format

    + +

    A matrix with upper case USDA soil classes as row names, and water tension +('pF1', 'pF2', 'pF 2.5') as column names

    +

    Source

    + +

    Anonymous (2014) Generic Guidance for Tier 1 FOCUS Ground Water Assessment +Version 2.2, May 2014 https://esdac.jrc.ec.europa.eu/projects/ground-water

    + +

    Examples

    + 
    focus_soil_moisture
+
    #>                 pF1 pF2 pF2.5
+#> Sand             24  12     7
+#> Loamy sand       24  14     9
+#> Sandy loam       27  19    15
+#> Sandy clay loam  28  22    18
+#> Clay loam        32  28    25
+#> Loam             31  25    21
+#> Silt loam        32  26    21
+#> Silty clay loam  34  30    27
+#> Silt             31  27    21
+#> Sandy clay       41  35    31
+#> Silty clay       44  40    36
+#> Clay             53  48    43
    +
    + +
    + + +
    +
    +

    Developed by Johannes Ranke.

    +
    + +
    +

    Site built with pkgdown 1.6.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/dev/reference/ilr.html b/docs/dev/reference/ilr.html index 8f58949e..98e51211 100644 --- a/docs/dev/reference/ilr.html +++ b/docs/dev/reference/ilr.html @@ -73,7 +73,7 @@ transformations." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ transformations." />
  • - + @@ -140,7 +140,7 @@ transformations." />

    Function to perform isometric log-ratio transformation

    - Source: R/ilr.R + Source: R/ilr.R
    @@ -149,9 +149,9 @@ transformations." /> transformations.

    - 
    ilr(x)
+    
    ilr(x)
 
-invilr(x)
    
+invilr(x)

    Arguments

    @@ -176,19 +176,33 @@ Compositional Data Using Robust Methods. Math Geosci 40 233-248

    Another implementation can be found in R package robCompositions.

    +

    Author

    + +

    René Lehmann and Johannes Ranke

    Examples

    
 # Order matters
-ilr(c(0.1, 1, 10))
    #> [1] -1.628174 -2.820079
    ilr(c(10, 1, 0.1))
    #> [1] 1.628174 2.820079
    # Equal entries give ilr transformations with zeros as elements
-ilr(c(3, 3, 3))
    #> [1] 0 0
    # Almost equal entries give small numbers
-ilr(c(0.3, 0.4, 0.3))
    #> [1] -0.2034219  0.1174457
    # Only the ratio between the numbers counts, not their sum
-invilr(ilr(c(0.7, 0.29, 0.01)))
    #> [1] 0.70 0.29 0.01
    invilr(ilr(2.1 * c(0.7, 0.29, 0.01)))
    #> [1] 0.70 0.29 0.01
    # Inverse transformation of larger numbers gives unequal elements
-invilr(-10)
    #> [1] 7.213536e-07 9.999993e-01
    invilr(c(-10, 0))
    #> [1] 7.207415e-07 9.991507e-01 8.486044e-04
    # The sum of the elements of the inverse ilr is 1
-sum(invilr(c(-10, 0)))
    #> [1] 1
    # This is why we do not need all elements of the inverse transformation to go back:
-a <- c(0.1, 0.3, 0.5)
-b <- invilr(a)
-length(b) # Four elements
    #> [1] 4
    ilr(c(b[1:3], 1 - sum(b[1:3]))) # Gives c(0.1, 0.3, 0.5)
    #> [1] 0.1 0.3 0.5
    
+ilr(c(0.1, 1, 10))
+
    #> [1] -1.628174 -2.820079
    ilr(c(10, 1, 0.1))
+
    #> [1] 1.628174 2.820079
    # Equal entries give ilr transformations with zeros as elements
+ilr(c(3, 3, 3))
+
    #> [1] 0 0
    # Almost equal entries give small numbers
+ilr(c(0.3, 0.4, 0.3))
+
    #> [1] -0.2034219  0.1174457
    # Only the ratio between the numbers counts, not their sum
+invilr(ilr(c(0.7, 0.29, 0.01)))
+
    #> [1] 0.70 0.29 0.01
    invilr(ilr(2.1 * c(0.7, 0.29, 0.01)))
+
    #> [1] 0.70 0.29 0.01
    # Inverse transformation of larger numbers gives unequal elements
+invilr(-10)
+
    #> [1] 7.213536e-07 9.999993e-01
    invilr(c(-10, 0))
+
    #> [1] 7.207415e-07 9.991507e-01 8.486044e-04
    # The sum of the elements of the inverse ilr is 1
+sum(invilr(c(-10, 0)))
+
    #> [1] 1
    # This is why we do not need all elements of the inverse transformation to go back:
+a <- c(0.1, 0.3, 0.5)
+b <- invilr(a)
+length(b) # Four elements
+
    #> [1] 4
    ilr(c(b[1:3], 1 - sum(b[1:3]))) # Gives c(0.1, 0.3, 0.5)
+
    #> [1] 0.1 0.3 0.5
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/index.html b/docs/dev/reference/index.html index 36c10225..cb37f9a6 100644 --- a/docs/dev/reference/index.html +++ b/docs/dev/reference/index.html @@ -163,7 +163,7 @@ @@ -373,6 +373,18 @@ of an mmkin object

    + + + + + + + + @@ -446,15 +458,15 @@ of an mmkin object

    - + @@ -484,7 +496,7 @@ of an mmkin object

    @@ -496,9 +508,9 @@ of an mmkin object

    - + kinetic models fitted with mkinfit

    - - - - @@ -524,12 +530,25 @@ kinetic models fitted with mkinfit

    mkin_long_to_wide()

    - + + + + + + + + + + + - + - - - - @@ -664,6 +677,12 @@ kinetic models fitted with mkinfit

    add_err()

    + + + + diff --git a/docs/dev/reference/logLik.mkinfit.html b/docs/dev/reference/logLik.mkinfit.html index 7ab36f0d..dbeeef60 100644 --- a/docs/dev/reference/logLik.mkinfit.html +++ b/docs/dev/reference/logLik.mkinfit.html @@ -76,7 +76,7 @@ the error model." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -124,7 +124,7 @@ the error model." />
    • - + @@ -143,7 +143,7 @@ the error model." />

      Calculated the log-likelihood of a fitted mkinfit object

      - Source: R/logLik.mkinfit.R + Source: R/logLik.mkinfit.R
      @@ -156,7 +156,7 @@ the error model.

      # S3 method for mkinfit
-logLik(object, ...)
      +logLik(object, ...)

      Arguments

    -

    mkinmod()

    +

    mkinmod() print(<mkinmod>) mkinsub()

    Function to set up a kinetic model with one or more state variables
    +

    focus_soil_moisture

    +

    FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar

    +

    D24_2014

    +

    Aerobic soil degradation data on 2,4-D from the EU assessment in 2014

    FOCUS_2006_A FOCUS_2006_B FOCUS_2006_C FOCUS_2006_D FOCUS_2006_E FOCUS_2006_F

    -

    mkinds

    +

    print(<mkinds>)

    A dataset class for mkin
    -

    print(<mkinds>)

    +

    print(<mkindsg>)

    Print mkinds objects

    A class for dataset groups for mkin
    -

    Helper functions mainly used internally

    +

    Utility functions
    -

    mkinsub()

    +

    f_time_norm_focus()

    Function to set up a kinetic submodel for one state variable

    Normalisation factors for aerobic soil degradation according to FOCUS guidance
    @@ -508,12 +520,6 @@ of an mmkin object
    -

    mkinpredict()

    -

    Produce predictions from a kinetic model using specific parameters

    mkin_wide_to_long()

    Convert a dataframe from long to wide format

    +

    Helper functions mainly used internally

    +

    +
    -

    print(<mkinmod>)

    +

    mkinpredict()

    Print mkinmod objects

    Produce predictions from a kinetic model using specific parameters
    @@ -544,12 +563,6 @@ kinetic models fitted with mkinfit

    Function to perform isometric log-ratio transformation
    -

    sigma_twocomp()

    -

    Two-component error model

    logLik(<mkinfit>)

    Add normally distributed errors to simulated kinetic degradation data

    +

    sigma_twocomp()

    +

    Two-component error model
    @@ -185,18 +185,26 @@ and the fitted error model parameters.

    Compare the AIC of columns of mmkin objects using AIC.mmkin.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
   # \dontrun{
-  sfo_sfo <- mkinmod(
-    parent = mkinsub("SFO", to = "m1"),
-    m1 = mkinsub("SFO")
-  )
    #> Successfully compiled differential equation model from auto-generated C code.
      d_t <- FOCUS_2006_D
-  f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity)
    #> Warning: Observations with value of zero were removed from the data
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
      f_obs <- mkinfit(sfo_sfo, d_t, error_model = "obs", quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
      f_tc <- mkinfit(sfo_sfo, d_t, error_model = "tc", quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
      AIC(f_nw, f_obs, f_tc)
    #>       df      AIC
+  sfo_sfo <- mkinmod(
+    parent = mkinsub("SFO", to = "m1"),
+    m1 = mkinsub("SFO")
+  )
+
    #> Successfully compiled differential equation model from auto-generated C code.
      d_t <- FOCUS_2006_D
+  f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity)
+
    #> Warning: Observations with value of zero were removed from the data
      f_obs <- mkinfit(sfo_sfo, d_t, error_model = "obs", quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
      f_tc <- mkinfit(sfo_sfo, d_t, error_model = "tc", quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
      AIC(f_nw, f_obs, f_tc)
+
    #>       df      AIC
 #> f_nw   5 204.4486
 #> f_obs  6 205.8727
-#> f_tc   6 141.9656
      # }
+#> f_tc   6 141.9656
      # }
    @@ -214,7 +222,7 @@ and the fitted error model parameters.

    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/logistic.solution-1.png b/docs/dev/reference/logistic.solution-1.png index fd11d0c0..84d8e722 100644 Binary files a/docs/dev/reference/logistic.solution-1.png and b/docs/dev/reference/logistic.solution-1.png differ diff --git a/docs/dev/reference/logistic.solution-2.png b/docs/dev/reference/logistic.solution-2.png index 78a31f93..764996df 100644 Binary files a/docs/dev/reference/logistic.solution-2.png and b/docs/dev/reference/logistic.solution-2.png differ diff --git a/docs/dev/reference/logistic.solution.html b/docs/dev/reference/logistic.solution.html index 248edcda..86be11a7 100644 --- a/docs/dev/reference/logistic.solution.html +++ b/docs/dev/reference/logistic.solution.html @@ -73,7 +73,7 @@ an increasing rate constant, supposedly caused by microbial growth" /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ an increasing rate constant, supposedly caused by microbial growth" />
    • - + @@ -140,7 +140,7 @@ an increasing rate constant, supposedly caused by microbial growth" />

      Logistic kinetics

      - Source: R/parent_solutions.R + Source: R/parent_solutions.R
      @@ -149,7 +149,7 @@ an increasing rate constant, supposedly caused by microbial growth" /> an increasing rate constant, supposedly caused by microbial growth

      - 
      logistic.solution(t, parent_0, kmax, k0, r)
      + 
      logistic.solution(t, parent_0, kmax, k0, r)

      Arguments

    @@ -208,30 +208,38 @@ Version 1.1, 18 December 2014

    Examples

    
   # Reproduce the plot on page 57 of FOCUS (2014)
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.2),
-       from = 0, to = 100, ylim = c(0, 100),
-       xlab = "Time", ylab = "Residue")
      plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.4),
-       from = 0, to = 100, add = TRUE, lty = 2, col = 2)
      plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.8),
-       from = 0, to = 100, add = TRUE, lty = 3, col = 3)
      plot(function(x) logistic.solution(x, 100, 0.08, 0.001, 0.2),
-       from = 0, to = 100, add = TRUE, lty = 4, col = 4)
      plot(function(x) logistic.solution(x, 100, 0.08, 0.08, 0.2),
-       from = 0, to = 100, add = TRUE, lty = 5, col = 5)
      legend("topright", inset = 0.05,
-         legend = paste0("k0 = ", c(0.0001, 0.0001, 0.0001, 0.001, 0.08),
-                         ", r = ", c(0.2, 0.4, 0.8, 0.2, 0.2)),
-         lty = 1:5, col = 1:5)
    
+  plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.2),
+       from = 0, to = 100, ylim = c(0, 100),
+       xlab = "Time", ylab = "Residue")
+
      plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.4),
+       from = 0, to = 100, add = TRUE, lty = 2, col = 2)
+
      plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.8),
+       from = 0, to = 100, add = TRUE, lty = 3, col = 3)
+
      plot(function(x) logistic.solution(x, 100, 0.08, 0.001, 0.2),
+       from = 0, to = 100, add = TRUE, lty = 4, col = 4)
+
      plot(function(x) logistic.solution(x, 100, 0.08, 0.08, 0.2),
+       from = 0, to = 100, add = TRUE, lty = 5, col = 5)
+
      legend("topright", inset = 0.05,
+         legend = paste0("k0 = ", c(0.0001, 0.0001, 0.0001, 0.001, 0.08),
+                         ", r = ", c(0.2, 0.4, 0.8, 0.2, 0.2)),
+         lty = 1:5, col = 1:5)
+
    
   # Fit with synthetic data
-  logistic <- mkinmod(parent = mkinsub("logistic"))
-
-  sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-  parms_logistic <- c(kmax = 0.08, k0 = 0.0001, r = 0.2)
-  d_logistic <- mkinpredict(logistic,
-    parms_logistic, c(parent = 100),
-    sampling_times)
-  d_2_1 <- add_err(d_logistic,
-    sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07),
-    n = 1, reps = 2, digits = 5, LOD = 0.1, seed = 123456)[[1]]
-
-  m <- mkinfit("logistic", d_2_1, quiet = TRUE)
-  plot_sep(m)
      summary(m)$bpar
    #>              Estimate   se_notrans   t value       Pr(>t)        Lower
+  logistic <- mkinmod(parent = mkinsub("logistic"))
+
+  sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+  parms_logistic <- c(kmax = 0.08, k0 = 0.0001, r = 0.2)
+  d_logistic <- mkinpredict(logistic,
+    parms_logistic, c(parent = 100),
+    sampling_times)
+  d_2_1 <- add_err(d_logistic,
+    sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07),
+    n = 1, reps = 2, digits = 5, LOD = 0.1, seed = 123456)[[1]]
+
+  m <- mkinfit("logistic", d_2_1, quiet = TRUE)
+  plot_sep(m)
+
      summary(m)$bpar
+
    #>              Estimate   se_notrans   t value       Pr(>t)        Lower
 #> parent_0 1.057896e+02 1.9023449703 55.610119 3.768361e-16 1.016451e+02
 #> kmax     6.398190e-02 0.0143201031  4.467978 3.841829e-04 3.929235e-02
 #> k0       1.612775e-04 0.0005866813  0.274898 3.940351e-01 5.846688e-08
@@ -242,7 +250,8 @@ Version 1.1, 18 December 2014
 #> kmax       0.1041853
 #> k0         0.4448749
 #> r          1.1821120
-#> sigma      7.3256566
      endpoints(m)$distimes
    #>            DT50     DT90  DT50_k0 DT50_kmax
+#> sigma      7.3256566
      endpoints(m)$distimes
+
    #>            DT50     DT90  DT50_k0 DT50_kmax
 #> parent 36.86533 62.41511 4297.853  10.83349
    @@ -260,7 +269,7 @@ Version 1.1, 18 December 2014
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/max_twa_parent.html b/docs/dev/reference/max_twa_parent.html index 01aab55d..25f745e9 100644 --- a/docs/dev/reference/max_twa_parent.html +++ b/docs/dev/reference/max_twa_parent.html @@ -78,7 +78,7 @@ soil section of the FOCUS guidance." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -126,7 +126,7 @@ soil section of the FOCUS guidance." />
    • - + @@ -146,7 +146,7 @@ soil section of the FOCUS guidance." />

      Function to calculate maximum time weighted average concentrations from kinetic models fitted with mkinfit

      - Source: R/max_twa_parent.R + Source: R/max_twa_parent.R
      @@ -158,15 +158,15 @@ FOMC, DFOP and HS models, using the analytical formulas given in the PEC soil section of the FOCUS guidance.

      - 
      max_twa_parent(fit, windows)
+    
      max_twa_parent(fit, windows)
 
-max_twa_sfo(M0 = 1, k, t)
+max_twa_sfo(M0 = 1, k, t)
 
-max_twa_fomc(M0 = 1, alpha, beta, t)
+max_twa_fomc(M0 = 1, alpha, beta, t)
 
-max_twa_dfop(M0 = 1, k1, k2, g, t)
+max_twa_dfop(M0 = 1, k1, k2, g, t)
 
-max_twa_hs(M0 = 1, k1, k2, tb, t)
      
+max_twa_hs(M0 = 1, k1, k2, tb, t)

      Arguments

    @@ -233,11 +233,15 @@ and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU Registration” Report of the FOCUS Work Group on Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

    +

    Author

    + +

    Johannes Ranke

    Examples

    
-  fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-  max_twa_parent(fit, c(7, 21))
    #>        7       21 
+  fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+  max_twa_parent(fit, c(7, 21))
+
    #>        7       21 
 #> 34.71343 18.22124
    @@ -255,7 +259,7 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mkinds.html b/docs/dev/reference/mkinds.html index a8641375..907f8ad3 100644 --- a/docs/dev/reference/mkinds.html +++ b/docs/dev/reference/mkinds.html @@ -75,7 +75,7 @@ provided by this package come as mkinds objects nevertheless." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -123,7 +123,7 @@ provided by this package come as mkinds objects nevertheless." />
    • - + @@ -142,7 +142,7 @@ provided by this package come as mkinds objects nevertheless." />

      A dataset class for mkin

      - Source: R/mkinds.R + Source: R/mkinds.R
      @@ -153,14 +153,29 @@ such as the on contained in the data field of mkinds objects. Some datasets provided by this package come as mkinds objects nevertheless.

      + 
      # S3 method for mkinds
+print(x, data = FALSE, ...)
      + +

      Arguments

      +
    + + + + + + + + + + + + + +
    x

    An mkinds object.

    data

    Should the data be printed?

    ...

    Not used.

    - -

    See also

    - -

    The S3 printing method print.mkinds

    Public fields

    -

    +

    title

    A full title for the dataset

    sampling_times

    The sampling times

    @@ -180,19 +195,19 @@ and value in order to be compatible with mkinfit

    Methods

    -

    Public methods

    +

    Public methods

    -

    Method new()

    -

    Create a new mkinds object

    Usage

    -

    mkinds$new(title = "", data, time_unit = NA, unit = NA)

    +

    Method new()

    +

    Create a new mkinds object

    Usage

    +

    mkinds$new(title = "", data, time_unit = NA, unit = NA)

    -

    Arguments

    -

    +

    Arguments

    +

    title

    The dataset title

    data

    The data

    @@ -203,12 +218,12 @@ and value in order to be compatible with mkinfit

    -

    Method clone()

    -

    The objects of this class are cloneable with this method.

    Usage

    -

    mkinds$clone(deep = FALSE)

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    Usage

    +

    mkinds$clone(deep = FALSE)

    -

    Arguments

    -

    +

    Arguments

    +

    deep

    Whether to make a deep clone.

    @@ -217,10 +232,12 @@ and value in order to be compatible with mkinfit

    Examples

    
-mds <- mkinds$new("FOCUS A", FOCUS_2006_A)
-print(mds)
    #> <mkinds> with $title:  FOCUS A 
+mds <- mkinds$new("FOCUS A", FOCUS_2006_A)
+print(mds)
+
    #> <mkinds> with $title:  FOCUS A 
 #> Observed compounds $observed:  parent 
-#> Sampling times $sampling_times:  0, 3, 7, 14, 30, 62, 90, 118 
+#> Sampling times $sampling_times:
+#> 0, 3, 7, 14, 30, 62, 90, 118 
 #> With a maximum of  1  replicates
    @@ -238,7 +255,7 @@ and value in order to be compatible with mkinfit

    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mkindsg.html b/docs/dev/reference/mkindsg.html new file mode 100644 index 00000000..3e4dfb39 --- /dev/null +++ b/docs/dev/reference/mkindsg.html @@ -0,0 +1,460 @@ + + + + + + + + +A class for dataset groups for mkin — mkindsg • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    +
    + + + + +
    + +
    +
    +
    +

    A class for dataset groups for mkin

    + Source: R/mkinds.R + +
    + +
    +

    A container for working with datasets that share at least one compound, +so that combined evaluations are desirable.

    +

    Time normalisation factors are initialised with a value of 1 for each +dataset if no data are supplied.

    +
    + + 
    # S3 method for mkindsg
+print(x, data = FALSE, verbose = data, ...)
    + +

    Arguments

    + + + + + + + + + + + + + + + + + + +
    x

    An mkindsg object.

    data

    Should the mkinds objects be printed with their data?

    verbose

    Should the mkinds objects be printed?

    ...

    Not used.

    + +

    Public fields

    + +

    +
    title

    A title for the dataset group

    + +
    ds

    A list of mkinds objects

    + +
    observed_n

    Occurrence counts of compounds in datasets

    + +
    f_time_norm

    Time normalisation factors

    + +
    meta

    A data frame with a row for each dataset, +containing additional information in the form +of categorical data (factors) or numerical data +(e.g. temperature, moisture, +or covariates like soil pH).

    + +

    +

    Methods

    + + +

    Public methods

    + + +

    +

    Method new()

    +

    Create a new mkindsg object

    Usage

    +

    mkindsg$new(title = "", ds, f_time_norm = rep(1, length(ds)), meta)

    + +

    Arguments

    +

    +
    title

    The title

    + +
    ds

    A list of mkinds objects

    + +
    f_time_norm

    Time normalisation factors

    + +
    meta

    The meta data

    + +

    +

    +

    Method clone()

    +

    The objects of this class are cloneable with this method.

    Usage

    +

    mkindsg$clone(deep = FALSE)

    + +

    Arguments

    +

    +
    deep

    Whether to make a deep clone.

    + +

    + + + +

    Examples

    + 
    
+mdsg <- mkindsg$new("Experimental X", experimental_data_for_UBA_2019[6:10])
+print(mdsg)
+
    #> <mkindsg> holding 5 mkinds objects
+#> Title $title:  Experimental X 
+#> Occurrene of observed compounds $observed_n:
+#> parent     A1 
+#>      5      5 
    print(mdsg, verbose = TRUE)
+
    #> <mkindsg> holding 5 mkinds objects
+#> Title $title:  Experimental X 
+#> Occurrene of observed compounds $observed_n:
+#> parent     A1 
+#>      5      5 
+#> 
+#> Datasets $ds:
+#> <mkinds> with $title:  Soil 6 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#> 
+#> <mkinds> with $title:  Soil 7 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 3, 7, 14, 30, 60, 90, 120, 180 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#> 
+#> <mkinds> with $title:  Soil 8 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 1, 3, 8, 14, 27, 48, 70 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#> 
+#> <mkinds> with $title:  Soil 9 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#> 
+#> <mkinds> with $title:  Soil 10 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 8, 14, 21, 41, 63, 91, 120 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
    print(mdsg, verbose = TRUE, data = TRUE)
+
    #> <mkindsg> holding 5 mkinds objects
+#> Title $title:  Experimental X 
+#> Occurrene of observed compounds $observed_n:
+#> parent     A1 
+#>      5      5 
+#> 
+#> Datasets $ds:
+#> <mkinds> with $title:  Soil 6 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#>    time parent   A1
+#> 1     0   97.2   NA
+#> 2     0   96.4   NA
+#> 3     3   71.1  4.3
+#> 4     3   69.2  4.6
+#> 5     6   58.1  7.0
+#> 6     6   56.6  7.2
+#> 7    10   44.4  8.2
+#> 8    10   43.4  8.0
+#> 9    20   33.3 11.0
+#> 10   20   29.2 13.7
+#> 11   34   17.6 11.5
+#> 12   34   18.0 12.7
+#> 13   55   10.5 14.9
+#> 14   55    9.3 14.5
+#> 15   90    4.5 12.1
+#> 16   90    4.7 12.3
+#> 17  112    3.0  9.9
+#> 18  112    3.4 10.2
+#> 19  132    2.3  8.8
+#> 20  132    2.7  7.8
+#> 
+#> <mkinds> with $title:  Soil 7 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 3, 7, 14, 30, 60, 90, 120, 180 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#>    time parent   A1
+#> 1     0   93.6   NA
+#> 2     0   92.3   NA
+#> 3     3   87.0  3.9
+#> 4     3   82.2  3.1
+#> 5     7   74.0  6.9
+#> 6     7   73.9  6.6
+#> 7    14   64.2 10.4
+#> 8    14   69.5  8.3
+#> 9    30   54.0 14.4
+#> 10   30   54.6 13.7
+#> 11   60   41.1 22.1
+#> 12   60   38.4 22.3
+#> 13   90   32.5 27.5
+#> 14   90   35.5 25.4
+#> 15  120   28.1 28.0
+#> 16  120   29.0 26.6
+#> 17  180   26.5 25.8
+#> 18  180   27.6 25.3
+#> 
+#> <mkinds> with $title:  Soil 8 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 1, 3, 8, 14, 27, 48, 70 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#>    time parent   A1
+#> 1     0   91.9   NA
+#> 2     0   90.8   NA
+#> 3     1   64.9  9.6
+#> 4     1   66.2  7.7
+#> 5     3   43.5 15.0
+#> 6     3   44.1 15.1
+#> 7     8   18.3 21.2
+#> 8     8   18.1 21.1
+#> 9    14   10.2 19.7
+#> 10   14   10.8 18.9
+#> 11   27    4.9 17.5
+#> 12   27    3.3 15.9
+#> 13   48    1.6  9.5
+#> 14   48    1.5  9.8
+#> 15   70    1.1  6.2
+#> 16   70    0.9  6.1
+#> 
+#> <mkinds> with $title:  Soil 9 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#>    time parent   A1
+#> 1     0   99.8   NA
+#> 2     0   98.3   NA
+#> 3     1   77.1  4.2
+#> 4     1   77.2  3.9
+#> 5     3   59.0  7.4
+#> 6     3   58.1  7.9
+#> 7     8   27.4 14.5
+#> 8     8   29.2 13.7
+#> 9    14   19.1 14.2
+#> 10   14   29.6 12.2
+#> 11   27   10.1 13.7
+#> 12   27   18.2 13.2
+#> 13   48    4.5 13.6
+#> 14   48    9.1 15.4
+#> 15   70    2.3 10.4
+#> 16   70    2.9 11.6
+#> 17   91    2.0 10.0
+#> 18   91    1.8  9.5
+#> 19  120    2.0  9.1
+#> 20  120    2.2  9.0
+#> 
+#> <mkinds> with $title:  Soil 10 
+#> Observed compounds $observed:  parent, A1 
+#> Sampling times $sampling_times:
+#> 0, 8, 14, 21, 41, 63, 91, 120 
+#> With a maximum of  2  replicates
+#> Time unit:  days 
+#> Observation unit:  \%AR 
+#>    time parent   A1
+#> 1     0   96.1   NA
+#> 2     0   94.3   NA
+#> 3     8   73.9  3.3
+#> 4     8   73.9  3.4
+#> 5    14   69.4  3.9
+#> 6    14   73.1  2.9
+#> 7    21   65.6  6.4
+#> 8    21   65.3  7.2
+#> 9    41   55.9  9.1
+#> 10   41   54.4  8.5
+#> 11   63   47.0 11.7
+#> 12   63   49.3 12.0
+#> 13   91   44.7 13.3
+#> 14   91   46.7 13.2
+#> 15  120   42.1 14.3
+#> 16  120   41.3 12.1
    
+
    +
    + +
    + + +
    +
    +

    Developed by Johannes Ranke.

    +
    + +
    +

    Site built with pkgdown 1.6.1.

    +
    + +
    +
    + + + + + + + + diff --git a/docs/dev/reference/mkinerrplot-1.png b/docs/dev/reference/mkinerrplot-1.png index c5d3495f..bae6071d 100644 Binary files a/docs/dev/reference/mkinerrplot-1.png and b/docs/dev/reference/mkinerrplot-1.png differ diff --git a/docs/dev/reference/mkinerrplot.html b/docs/dev/reference/mkinerrplot.html index 104d1e3a..48d20ca8 100644 --- a/docs/dev/reference/mkinerrplot.html +++ b/docs/dev/reference/mkinerrplot.html @@ -76,7 +76,7 @@ using the argument show_errplot = TRUE." /> mkin - 0.9.50.3 + 0.9.50.4
    @@ -124,7 +124,7 @@ using the argument show_errplot = TRUE." />
  • - + @@ -143,7 +143,7 @@ using the argument show_errplot = TRUE." />

    Function to plot squared residuals and the error model for an mkin object

    - Source: R/mkinerrplot.R + Source: R/mkinerrplot.R
    @@ -155,20 +155,20 @@ and this error model plot can be obtained with show_errplot = TRUE.

    - 
    mkinerrplot(
-  object,
-  obs_vars = names(object$mkinmod$map),
-  xlim = c(0, 1.1 * max(object$data$predicted)),
-  xlab = "Predicted",
-  ylab = "Squared residual",
-  maxy = "auto",
-  legend = TRUE,
-  lpos = "topright",
-  col_obs = "auto",
-  pch_obs = "auto",
-  frame = TRUE,
-  ...
-)
    + 
    mkinerrplot(
+  object,
+  obs_vars = names(object$mkinmod$map),
+  xlim = c(0, 1.1 * max(object$data$predicted)),
+  xlab = "Predicted",
+  ylab = "Squared residual",
+  maxy = "auto",
+  legend = TRUE,
+  lpos = "topright",
+  col_obs = "auto",
+  pch_obs = "auto",
+  frame = TRUE,
+  ...
+)

    Arguments

    @@ -223,7 +223,7 @@ be passed on to legend - +
    ...

    further arguments passed to plot.

    further arguments passed to plot.
    @@ -235,11 +235,17 @@ effect, namely to produce a plot.

    mkinplot, for a way to plot the data and the fitted lines of the mkinfit object.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # \dontrun{
-model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
    mkinerrplot(fit)
    # }
+model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
    mkinerrplot(fit)
+
    # }
    @@ -257,7 +263,7 @@ lines of the mkinfit object.

    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mkinfit.html b/docs/dev/reference/mkinfit.html index b46c2cce..f5a913b2 100644 --- a/docs/dev/reference/mkinfit.html +++ b/docs/dev/reference/mkinfit.html @@ -432,15 +432,15 @@ Degradation Data. Environments 6(12) 124 summary(fit)
    #> mkin version used for fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Thu Nov 5 23:14:40 2020 -#> Date of summary: Thu Nov 5 23:14:40 2020 +#> Date of fit: Thu Nov 19 14:49:38 2020 +#> Date of summary: Thu Nov 19 14:49:38 2020 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 222 model solutions performed in 0.05 s +#> Fitted using 222 model solutions performed in 0.045 s #> #> Error model: Constant variance #> @@ -573,10 +573,10 @@ Degradation Data. Environments 6(12) 124 analytical = mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE, error_model = "tc", solution_type = "analytical")) } -
    #> Loading required package: rbenchmark
    #> test relative elapsed -#> 3 analytical 1.000 0.532 -#> 1 deSolve_compiled 1.765 0.939 -#> 2 eigen 2.229 1.186
    # } +
    #> test relative elapsed +#> 3 analytical 1.000 0.534 +#> 1 deSolve_compiled 1.908 1.019 +#> 2 eigen 2.238 1.195
    # } # Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO # \dontrun{ @@ -600,8 +600,8 @@ Degradation Data. Environments 6(12) 124 summary(fit.FOMC_SFO.tc, data = FALSE)
    #> Warning: NaNs produced
    #> Warning: NaNs produced
    #> Warning: NaNs produced
    #> Warning: diag(.) had 0 or NA entries; non-finite result is doubtful
    #> mkin version used for fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Thu Nov 5 23:14:51 2020 -#> Date of summary: Thu Nov 5 23:14:51 2020 +#> Date of fit: Thu Nov 19 14:49:49 2020 +#> Date of summary: Thu Nov 19 14:49:49 2020 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent @@ -610,7 +610,7 @@ Degradation Data. Environments 6(12) 124 #> #> Model predictions using solution type deSolve #> -#> Fitted using 4273 model solutions performed in 3.081 s +#> Fitted using 4273 model solutions performed in 3.1 s #> #> Error model: Two-component variance function #> diff --git a/docs/dev/reference/mkinmod.html b/docs/dev/reference/mkinmod.html index 42529747..979e653a 100644 --- a/docs/dev/reference/mkinmod.html +++ b/docs/dev/reference/mkinmod.html @@ -42,7 +42,11 @@ +(see examples). +Print mkinmod objects in a way that the user finds his way to get to its +components. +This is a convenience function to set up the lists used as arguments for +mkinmod." /> @@ -74,7 +78,7 @@ variable, specifying the corresponding submodel as well as outgoing pathways mkin - 0.9.50.3 + 0.9.50.4
    @@ -122,7 +126,7 @@ variable, specifying the corresponding submodel as well as outgoing pathways
  • - + @@ -141,50 +145,60 @@ variable, specifying the corresponding submodel as well as outgoing pathways

    Function to set up a kinetic model with one or more state variables

    - Source: R/mkinmod.R + Source: R/mkinmod.R, R/mkinsub.R
    -

    This function is usually called using a call to mkinsub() for each observed +

    This function is usually called using a call to mkinsub() for each observed variable, specifying the corresponding submodel as well as outgoing pathways (see examples).

    +

    Print mkinmod objects in a way that the user finds his way to get to its +components.

    +

    This is a convenience function to set up the lists used as arguments for +mkinmod.

    - 
    mkinmod(
-  ...,
-  use_of_ff = "max",
-  speclist = NULL,
-  quiet = FALSE,
-  verbose = FALSE
-)
    + 
    mkinmod(
+  ...,
+  use_of_ff = "max",
+  speclist = NULL,
+  quiet = FALSE,
+  verbose = FALSE
+)
+
+# S3 method for mkinmod
+print(x, ...)
+
+mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)

    Arguments

    - +additional mkinsub() argument can be sink = FALSE, effectively +fixing the flux to sink to zero. +In print.mkinmod, this argument is currently not used.

    +model equations and, if applicable, the coefficient matrix. If "max", +formation fractions are always used (default). If "min", a minimum use of +formation fractions is made, i.e. each pathway to a metabolite has its +own rate constant.

    @@ -200,6 +214,32 @@ argument. Default is NULL.

    + + + + + + + + + + + + + + + + + + + +
    ...

    For each observed variable, a list as obtained by mkinsub() +

    For each observed variable, a list as obtained by mkinsub() has to be specified as an argument (see examples). Currently, single first order kinetics "SFO", indeterminate order rate equation kinetics "IORE", or single first order with reversible binding "SFORB" are implemented for all variables, while "FOMC", "DFOP", "HS" and "logistic" can additionally be chosen for the first variable which is assumed to be the source compartment. -Additionally, mkinsub() has an argument to, specifying names of +Additionally, mkinsub() has an argument to, specifying names of variables to which a transfer is to be assumed in the model. If the argument use_of_ff is set to "min" (default) and the model for the compartment is "SFO" or "SFORB", an -additional mkinsub() argument can be sink = FALSE, effectively -fixing the flux to sink to zero.
    use_of_ff

    Specification of the use of formation fractions in the -model equations and, if applicable, the coefficient matrix. If "min", a -minimum use of formation fractions is made in order to avoid fitting the -product of formation fractions and rate constants. If "max", formation -fractions are always used.
    speclist verbose

    If TRUE, passed to inline::cfunction() if applicable to give detailed information about the C function being built.

    x

    An mkinmod object.

    submodel

    Character vector of length one to specify the submodel type. +See mkinmod for the list of allowed submodel names.

    to

    Vector of the names of the state variable to which a +transformation shall be included in the model.

    sink

    Should a pathway to sink be included in the model in addition to +the pathways to other state variables?

    full_name

    An optional name to be used e.g. for plotting fits +performed with the model. You can use non-ASCII characters here, but then +your R code will not be portable, i.e. may produce unintended plot +results on other operating systems or system configurations.
    @@ -219,6 +259,8 @@ represented by one.

    cf

    If generated, a compiled function calculating the derivatives as returned by cfunction.

    +A list for use with mkinmod. +

    Details

    For the definition of model types and their parameters, the equations given @@ -244,27 +286,36 @@ EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics

    NAFTA Technical Working Group on Pesticides (not dated) Guidance for Evaluating and Calculating Degradation Kinetics in Environmental Media

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # Specify the SFO model (this is not needed any more, as we can now mkinfit("SFO", ...)
-SFO <- mkinmod(parent = mkinsub("SFO"))
+SFO <- mkinmod(parent = mkinsub("SFO"))
 
 # One parent compound, one metabolite, both single first order
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # \dontrun{
+# Now supplying full names used for plotting
+ SFO_SFO.2 <- mkinmod(
+   parent = mkinsub("SFO", "m1", full_name = "Test compound"),
+   m1 = mkinsub("SFO", full_name = "Metabolite M1"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # 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.
    
+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 file306f74383fd2.c 2> file306f74383fd2.c.err.txt 
-#> Program source:
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"), verbose = TRUE)
+
    #> Program source:
 #>   1: #include <R.h>
 #>   2: 
 #>   3: 
@@ -286,7 +337,8 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media
    
 #>  19: }
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # The symbolic solution which is available in this case is not
 # made for human reading but for speed of computation
-SFO_SFO$deg_func
    #> function (observed, odeini, odeparms) 
+SFO_SFO$deg_func
+
    #> function (observed, odeini, odeparms) 
 #> {
 #>     predicted <- numeric(0)
 #>     with(as.list(odeparms), {
@@ -301,19 +353,41 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media
    
 #>     })
 #>     return(predicted)
 #> }
-#> <environment: 0x55555ad56ea0>
    
+#> <environment: 0x55555cb0b088>
    
 # 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]]$data,
-  quiet = TRUE)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.000174
    # }
-
+m_synth_DFOP_par <- mkinmod(
+ parent = mkinsub("DFOP", c("M1", "M2")),
+ M1 = mkinsub("SFO"),
+ M2 = mkinsub("SFO"),
+ quiet = TRUE)
+
+fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par,
+  synthetic_data_for_UBA_2014[[12]]$data,
+  quiet = TRUE)
+# }
+
+
+  m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
+                             M1 = list(type = "SFO", to = "M2"),
+                             M2 = list(type = "SFO"), use_of_ff = "max")
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
+  print(m_synth_SFO_lin)
+
    #> <mkinmod> model generated with
+#> Use of formation fractions $use_of_ff: max 
+#> Specification $spec:
+#> $parent
+#> $type: SFO; $to: M1; $sink: TRUE
+#> $M1
+#> $type: SFO; $to: M2; $sink: TRUE
+#> $M2
+#> $type: SFO; $sink: TRUE
+#> Coefficient matrix $coefmat available
+#> Compiled model $cf available
+#> Differential equations:
+#> d_parent/dt = - k_parent * parent
+#> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1
+#> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mkinparplot-1.png b/docs/dev/reference/mkinparplot-1.png index 6853a4ba..dcf3e4b5 100644 Binary files a/docs/dev/reference/mkinparplot-1.png and b/docs/dev/reference/mkinparplot-1.png differ diff --git a/docs/dev/reference/mkinparplot.html b/docs/dev/reference/mkinparplot.html index 027d8ae9..e237ecae 100644 --- a/docs/dev/reference/mkinparplot.html +++ b/docs/dev/reference/mkinparplot.html @@ -73,7 +73,7 @@ mkinfit." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ mkinfit." />
  • - + @@ -140,7 +140,7 @@ mkinfit." />

    Function to plot the confidence intervals obtained using mkinfit

    - Source: R/mkinparplot.R + Source: R/mkinparplot.R
    @@ -149,7 +149,7 @@ mkinfit." /> mkinfit.

    - 
    mkinparplot(object)
    + 
    mkinparplot(object)

    Arguments

    @@ -164,14 +164,20 @@ mkinfit." />

    Nothing is returned by this function, as it is called for its side effect, namely to produce a plot.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # \dontrun{
-model <- mkinmod(
-  T245 = mkinsub("SFO", to = c("phenol"), sink = FALSE),
-  phenol = mkinsub("SFO", to = c("anisole")),
-  anisole = mkinsub("SFO"), use_of_ff = "max")
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
    mkinparplot(fit)
    # }
+model <- mkinmod(
+  T245 = mkinsub("SFO", to = c("phenol"), sink = FALSE),
+  phenol = mkinsub("SFO", to = c("anisole")),
+  anisole = mkinsub("SFO"), use_of_ff = "max")
+
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
    mkinparplot(fit)
+
    # }
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mkinpredict.html b/docs/dev/reference/mkinpredict.html index 7d522eb1..d3a86276 100644 --- a/docs/dev/reference/mkinpredict.html +++ b/docs/dev/reference/mkinpredict.html @@ -407,11 +407,11 @@ as these always return mapped output.

    c(parent =100, m1 =0), seq(0, 20, by =0.1), solution_type ="analytical", use_compiled =FALSE)[201,])} -
    #> Loading required package: rbenchmark
    #> test relative elapsed +
    #> test relative elapsed #> 2 deSolve_compiled 1.0 0.005 +#> 4 analytical 1.0 0.005 #> 1 eigen 4.0 0.020 -#> 4 analytical 4.0 0.020 -#> 3 deSolve 45.6 0.228
    +#> 3 deSolve 44.6 0.223
    # \dontrun{ # Predict from a fitted model f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE) diff --git a/docs/dev/reference/mkinresplot-1.png b/docs/dev/reference/mkinresplot-1.png index bb9657b4..ffd34f6f 100644 Binary files a/docs/dev/reference/mkinresplot-1.png and b/docs/dev/reference/mkinresplot-1.png differ diff --git a/docs/dev/reference/mkinresplot.html b/docs/dev/reference/mkinresplot.html index 5591d26f..38c52425 100644 --- a/docs/dev/reference/mkinresplot.html +++ b/docs/dev/reference/mkinresplot.html @@ -75,7 +75,7 @@ argument show_residuals = TRUE." /> mkin - 0.9.50.3 + 0.9.50.4
    @@ -123,7 +123,7 @@ argument show_residuals = TRUE." />
    • - + @@ -142,7 +142,7 @@ argument show_residuals = TRUE." />

      Function to plot residuals stored in an mkin object

      - Source: R/mkinresplot.R + Source: R/mkinresplot.R
      @@ -153,21 +153,21 @@ the residuals can be obtained using plot.mkinf argument show_residuals = TRUE.

      - 
      mkinresplot(
-  object,
-  obs_vars = names(object$mkinmod$map),
-  xlim = c(0, 1.1 * max(object$data$time)),
-  standardized = FALSE,
-  xlab = "Time",
-  ylab = ifelse(standardized, "Standardized residual", "Residual"),
-  maxabs = "auto",
-  legend = TRUE,
-  lpos = "topright",
-  col_obs = "auto",
-  pch_obs = "auto",
-  frame = TRUE,
-  ...
-)
      + 
      mkinresplot(
+  object,
+  obs_vars = names(object$mkinmod$map),
+  xlim = c(0, 1.1 * max(object$data$time)),
+  standardized = FALSE,
+  xlab = "Time",
+  ylab = ifelse(standardized, "Standardized residual", "Residual"),
+  maxabs = "auto",
+  legend = TRUE,
+  lpos = "topright",
+  col_obs = "auto",
+  pch_obs = "auto",
+  frame = TRUE,
+  ...
+)

      Arguments

    @@ -227,7 +227,7 @@ be passed on to legend - +
    ...

    further arguments passed to plot.

    further arguments passed to plot.
    @@ -240,10 +240,16 @@ effect, namely to produce a plot.

    mkinplot, for a way to plot the data and the fitted lines of the mkinfit object, and plot_res for a function combining the plot of the fit and the residual plot.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
-model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, FOCUS_2006_D, quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    mkinresplot(fit, "m1")
    
+model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(model, FOCUS_2006_D, quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
    mkinresplot(fit, "m1")
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mkinsub.html b/docs/dev/reference/mkinsub.html index 585e1840..68fd6268 100644 --- a/docs/dev/reference/mkinsub.html +++ b/docs/dev/reference/mkinsub.html @@ -73,7 +73,7 @@ mkinmod." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -121,7 +121,7 @@ mkinmod." />
  • - + @@ -140,7 +140,7 @@ mkinmod." />

    Function to set up a kinetic submodel for one state variable

    - Source: R/mkinsub.R + Source: R/mkinsub.R
    @@ -149,7 +149,7 @@ mkinmod." /> mkinmod.

    - 
    mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)
    + 
    mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)

    Arguments

    @@ -181,22 +181,28 @@ results on other operating systems or system configurations.

    Value

    A list for use with mkinmod.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # One parent compound, one metabolite, both single first order.
-SFO_SFO <- mkinmod(
-  parent = list(type = "SFO", to = "m1"),
-  m1 = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+SFO_SFO <- mkinmod(
+  parent = list(type = "SFO", to = "m1"),
+  m1 = list(type = "SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # The same model using mkinsub
-SFO_SFO.2 <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    
+SFO_SFO.2 <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    
 # \dontrun{
   # Now supplying full names
-  SFO_SFO.2 <- mkinmod(
-    parent = mkinsub("SFO", "m1", full_name = "Test compound"),
-    m1 = mkinsub("SFO", full_name = "Metabolite M1"))
    #> Successfully compiled differential equation model from auto-generated C code.
     # }
+  SFO_SFO.2 <- mkinmod(
+    parent = mkinsub("SFO", "m1", full_name = "Test compound"),
+    m1 = mkinsub("SFO", full_name = "Metabolite M1"))
+
    #> Successfully compiled differential equation model from auto-generated C code.
     # }
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/mmkin.html b/docs/dev/reference/mmkin.html index b0ca90f0..4786b02e 100644 --- a/docs/dev/reference/mmkin.html +++ b/docs/dev/reference/mmkin.html @@ -227,9 +227,9 @@ plotting.

    time_default
    #> user system elapsed -#> 4.706 0.488 1.375
    time_1 +#> 4.664 0.433 1.317
    time_1
    #> user system elapsed -#> 5.232 0.005 5.238
    +#> 5.326 0.001 5.330
    endpoints(fits.0[["SFO_lin", 2]])
    #> $ff #> parent_M1 parent_sink M1_M2 M1_sink @@ -252,7 +252,29 @@ plotting.

    # Plotting with mmkin (single brackets, extracting an mmkin object) does not# allow to plot the observed variables separatelyplot(fits.0[1, 1]) -
    # } +
    +# On Windows, we can use multiple cores by making a cluster using the parallel +# package, which gets loaded with mkin, and passing it to mmkin, e.g. +cl <- makePSOCKcluster(12) +f <- mmkin(c("SFO", "FOMC", "DFOP"), + list(A = FOCUS_2006_A, B = FOCUS_2006_B, C = FOCUS_2006_C, D = FOCUS_2006_D), + cluster = cl, quiet = TRUE) +print(f) +
    #> <mmkin> object +#> Status of individual fits: +#> +#> dataset +#> model A B C D +#> SFO OK OK OK OK +#> FOMC C OK OK OK +#> DFOP OK OK OK OK +#> +#> OK: No warnings +#> C: Optimisation did not converge: +#> false convergence (8)
    # We get false convergence for the FOMC fit to FOCUS_2006_A because this +# dataset is really SFO, and the FOMC fit is overparameterised +stopCluster(cl) +# }
    diff --git a/docs/dev/reference/nafta-1.png b/docs/dev/reference/nafta-1.png index 9025f2bb..4d823d77 100644 Binary files a/docs/dev/reference/nafta-1.png and b/docs/dev/reference/nafta-1.png differ diff --git a/docs/dev/reference/nafta.html b/docs/dev/reference/nafta.html index 690e4827..bbc8797d 100644 --- a/docs/dev/reference/nafta.html +++ b/docs/dev/reference/nafta.html @@ -76,7 +76,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -124,7 +124,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." />
    • - + @@ -143,7 +143,7 @@ order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP." />

      Evaluate parent kinetics using the NAFTA guidance

      - Source: R/nafta.R + Source: R/nafta.R
      @@ -155,10 +155,10 @@ and plotting.

      order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP.

      - 
      nafta(ds, title = NA, quiet = FALSE, ...)
+    
      nafta(ds, title = NA, quiet = FALSE, ...)
 
 # S3 method for nafta
-print(x, quiet = TRUE, digits = 3, ...)
      
+print(x, quiet = TRUE, digits = 3, ...)

      Arguments

    @@ -211,10 +211,15 @@ Degradation mmkin object containing the fits of the three models. The list element named "title" contains the title of the dataset used. The list element "data" contains the dataset used in the fits.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
-  nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00192
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00258
    #> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    #> The representative half-life of the IORE model is longer than the one corresponding
    #> to the terminal degradation rate found with the DFOP model.
    #> The representative half-life obtained from the DFOP model may be used
      print(nafta_evaluation)
    #> Sums of squares:
+  nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
+
    #> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    #> The representative half-life of the IORE model is longer than the one corresponding
    #> to the terminal degradation rate found with the DFOP model.
    #> The representative half-life obtained from the DFOP model may be used
      print(nafta_evaluation)
+
    #> Sums of squares:
 #>       SFO      IORE      DFOP 
 #> 1378.6832  615.7730  517.8836 
 #> 
@@ -251,7 +256,8 @@ list element "data" contains the dataset used in the fits.
    
 #> DFOP  429    2380      841
 #> 
 #> Representative half-life:
-#> [1] 841.41
      plot(nafta_evaluation)
    
+#> [1] 841.41
      plot(nafta_evaluation)
+
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/nlme-1.png b/docs/dev/reference/nlme-1.png index 0b34db8f..193722c7 100644 Binary files a/docs/dev/reference/nlme-1.png and b/docs/dev/reference/nlme-1.png differ diff --git a/docs/dev/reference/nlme-2.png b/docs/dev/reference/nlme-2.png index ce932c86..7129c580 100644 Binary files a/docs/dev/reference/nlme-2.png and b/docs/dev/reference/nlme-2.png differ diff --git a/docs/dev/reference/nlme.html b/docs/dev/reference/nlme.html index e21074e7..e109b34e 100644 --- a/docs/dev/reference/nlme.html +++ b/docs/dev/reference/nlme.html @@ -226,28 +226,28 @@ nlme for the case of a single grouping variable ds.

    #> Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) #> Data: grouped_data #> AIC BIC logLik -#> 298.2781 307.7372 -144.1391 +#> 252.7798 262.1358 -121.3899 #> #> Random effects: #> Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1) #> Level: ds #> Structure: Diagonal -#> parent_0 log_k_parent_sink Residual -#> StdDev: 0.9374733 0.7098105 3.83543 +#> parent_0 log_k_parent_sink Residual +#> StdDev: 0.0006768135 0.6800777 2.489397 #> #> Fixed effects: parent_0 + log_k_parent_sink ~ 1 -#> Value Std.Error DF t-value p-value -#> parent_0 101.76838 1.1445444 45 88.91606 0 -#> log_k_parent_sink -3.05444 0.4195622 45 -7.28008 0 +#> Value Std.Error DF t-value p-value +#> parent_0 101.74884 0.6456014 44 157.60321 0 +#> log_k_parent_sink -3.05575 0.4015811 44 -7.60929 0 #> Correlation: #> prnt_0 -#> log_k_parent_sink 0.034 +#> log_k_parent_sink 0.026 #> #> Standardized Within-Group Residuals: #> Min Q1 Med Q3 Max -#> -2.6169360 -0.2185329 0.0574070 0.5720937 3.0459868 +#> -2.1317488 -0.6878121 0.0828385 0.8592270 2.9529864 #> -#> Number of Observations: 49 +#> Number of Observations: 48 #> Number of Groups: 3
    plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
    # augPred does not work on fits with more than one state # variable diff --git a/docs/dev/reference/nlme.mmkin.html b/docs/dev/reference/nlme.mmkin.html index 05edbde5..84990521 100644 --- a/docs/dev/reference/nlme.mmkin.html +++ b/docs/dev/reference/nlme.mmkin.html @@ -332,12 +332,12 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> StdDev: 0.002417 21.63 #>
    ds_2 <- lapply(experimental_data_for_UBA_2019[6:10], function(x) x$data[c("name", "time", "value")]) - m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), - A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE) - m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"), - A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) - m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), - A1 = mkinsub("SFO"), quiet = TRUE) + m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), + A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE) + m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"), + A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE) + m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), + A1 = mkinsub("SFO"), quiet = TRUE) f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo, "SFO-SFO-ff" = m_sfo_sfo_ff, diff --git a/docs/dev/reference/parms.html b/docs/dev/reference/parms.html index bd35d3c1..ba0e89bb 100644 --- a/docs/dev/reference/parms.html +++ b/docs/dev/reference/parms.html @@ -74,7 +74,7 @@ considering the error structure that was assumed for the fit." /> mkin - 0.9.50.3 + 0.9.50.4
    @@ -122,7 +122,7 @@ considering the error structure that was assumed for the fit." />
    • - + @@ -141,7 +141,7 @@ considering the error structure that was assumed for the fit." />

      Extract model parameters from mkinfit models

      - Source: R/parms.mkinfit.R + Source: R/parms.mkinfit.R
      @@ -151,13 +151,13 @@ model parameters, in order to avoid working with a fitted model without considering the error structure that was assumed for the fit.

      - 
      parms(object, ...)
+    
      parms(object, ...)
 
 # S3 method for mkinfit
-parms(object, transformed = FALSE, ...)
+parms(object, transformed = FALSE, ...)
 
 # S3 method for mmkin
-parms(object, transformed = FALSE, ...)
      
+parms(object, transformed = FALSE, ...)

      Arguments

    @@ -187,19 +187,24 @@ such matrices is returned.

    Examples

    # mkinfit objects
-fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
-parms(fit)
    #>   parent_0   k_parent      sigma 
-#> 82.4921598  0.3060633  4.6730124 
    parms(fit, transformed = TRUE)
    #>     parent_0 log_k_parent        sigma 
+fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
+parms(fit)
+
    #>   parent_0   k_parent      sigma 
+#> 82.4921598  0.3060633  4.6730124 
    parms(fit, transformed = TRUE)
+
    #>     parent_0 log_k_parent        sigma 
 #>    82.492160    -1.183963     4.673012 
    
 # mmkin objects
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
+ds <- lapply(experimental_data_for_UBA_2019[6:10],
+ function(x) subset(x$data[c("name", "time", "value")]))
+names(ds) <- paste("Dataset", 6:10)
 # \dontrun{
-fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0195
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00408
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0492
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00985
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.00815
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.011
    parms(fits["SFO", ])
    #>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
+fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
+parms(fits["SFO", ])
+
    #>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
 #> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450
 #> k_parent  0.05794659  0.009647805  0.2102974  0.1232258  0.00720421
-#> sigma     5.15274487  7.040168584  3.6769645  6.4669234  6.50457673
    parms(fits[, 2])
    #> $SFO
+#> sigma     5.15274487  7.040168584  3.6769645  6.4669234  6.50457673
    parms(fits[, 2])
+
    #> $SFO
 #>             Dataset 7
 #> parent_0 82.666781678
 #> k_parent  0.009647805
@@ -214,12 +219,13 @@ such matrices is returned.
    
 #> 
 #> $DFOP
 #>             Dataset 7
-#> parent_0 91.058971503
+#> parent_0 91.058971597
 #> k1        0.044946770
 #> k2        0.002868336
-#> g         0.526942415
+#> g         0.526942414
 #> sigma     2.221302196
-#> 
    parms(fits)
    #> $SFO
+#> 
    parms(fits)
+
    #> $SFO
 #>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
 #> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450
 #> k_parent  0.05794659  0.009647805  0.2102974  0.1232258  0.00720421
@@ -234,12 +240,13 @@ such matrices is returned.
    
 #> 
 #> $DFOP
 #>            Dataset 6    Dataset 7   Dataset 8   Dataset 9   Dataset 10
-#> parent_0 96.55213663 91.058971503 90.34509469 98.14858850 94.311323409
-#> k1        0.21954589  0.044946770  0.41232289  0.31697588  0.080663853
-#> k2        0.02957934  0.002868336  0.07581767  0.03260384  0.003425417
-#> g         0.44845068  0.526942415  0.66091965  0.65322767  0.342652880
+#> parent_0 96.55213663 91.058971597 90.34509493 98.14858820 94.311323733
+#> k1        0.21954588  0.044946770  0.41232288  0.31697588  0.080663857
+#> k2        0.02957934  0.002868336  0.07581766  0.03260384  0.003425417
+#> g         0.44845068  0.526942414  0.66091967  0.65322767  0.342652880
 #> sigma     1.35690468  2.221302196  1.34169076  2.87159846  1.942067831
-#> 
    parms(fits, transformed = TRUE)
    #> $SFO
+#> 
    parms(fits, transformed = TRUE)
+
    #> $SFO
 #>              Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10
 #> parent_0     88.522754 82.666782 86.854731 91.777931  82.148094
 #> log_k_parent -2.848234 -4.641025 -1.559232 -2.093737  -4.933090
@@ -253,13 +260,13 @@ such matrices is returned.
    
 #> sigma      1.8476712  1.9167519  1.0660627  3.14605557   1.622278
 #> 
 #> $DFOP
-#>           Dataset 6   Dataset 7  Dataset 8  Dataset 9 Dataset 10
-#> parent_0 96.5521366 91.05897150 90.3450947 98.1485885  94.311323
-#> log_k1   -1.5161940 -3.10227638 -0.8859485 -1.1489296  -2.517465
-#> log_k2   -3.5206791 -5.85402317 -2.5794240 -3.4233253  -5.676532
-#> g_ilr    -0.1463234  0.07627854  0.4719196  0.4477805  -0.460676
-#> sigma     1.3569047  2.22130220  1.3416908  2.8715985   1.942068
-#> 
    # }
+#>           Dataset 6  Dataset 7  Dataset 8  Dataset 9 Dataset 10
+#> parent_0 96.5521366 91.0589716 90.3450949 98.1485882 94.3113237
+#> log_k1   -1.5161940 -3.1022764 -0.8859486 -1.1489296 -2.5174647
+#> log_k2   -3.5206791 -5.8540232 -2.5794240 -3.4233253 -5.6765322
+#> g_qlogis -0.2069326  0.1078741  0.6673953  0.6332573 -0.6514943
+#> sigma     1.3569047  2.2213022  1.3416908  2.8715985  1.9420678
+#> 
    # }
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/plot.mixed.mmkin-3.png b/docs/dev/reference/plot.mixed.mmkin-3.png index 67058e6c..d58b9c69 100644 Binary files a/docs/dev/reference/plot.mixed.mmkin-3.png and b/docs/dev/reference/plot.mixed.mmkin-3.png differ diff --git a/docs/dev/reference/plot.mixed.mmkin.html b/docs/dev/reference/plot.mixed.mmkin.html index 4108aea3..6ed7cbba 100644 --- a/docs/dev/reference/plot.mixed.mmkin.html +++ b/docs/dev/reference/plot.mixed.mmkin.html @@ -277,10 +277,10 @@ corresponding model prediction lines for the different datasets.

    f_saem <- saem(f)
    #> Running main SAEM algorithm -#> [1] "Mon Nov 9 17:18:17 2020" +#> [1] "Thu Nov 19 14:51:14 2020" #> .... #> Minimisation finished -#> [1] "Mon Nov 9 17:18:26 2020"
    plot(f_saem) +#> [1] "Thu Nov 19 14:51:24 2020"
    plot(f_saem)
    # }
    diff --git a/docs/dev/reference/plot.mkinfit-1.png b/docs/dev/reference/plot.mkinfit-1.png index c6a415d7..fc195031 100644 Binary files a/docs/dev/reference/plot.mkinfit-1.png and b/docs/dev/reference/plot.mkinfit-1.png differ diff --git a/docs/dev/reference/plot.mkinfit-2.png b/docs/dev/reference/plot.mkinfit-2.png index 5dd3731e..fa99f680 100644 Binary files a/docs/dev/reference/plot.mkinfit-2.png and b/docs/dev/reference/plot.mkinfit-2.png differ diff --git a/docs/dev/reference/plot.mkinfit-3.png b/docs/dev/reference/plot.mkinfit-3.png index 59cf8f8d..28789544 100644 Binary files a/docs/dev/reference/plot.mkinfit-3.png and b/docs/dev/reference/plot.mkinfit-3.png differ diff --git a/docs/dev/reference/plot.mkinfit-4.png b/docs/dev/reference/plot.mkinfit-4.png index d9867952..77b3422f 100644 Binary files a/docs/dev/reference/plot.mkinfit-4.png and b/docs/dev/reference/plot.mkinfit-4.png differ diff --git a/docs/dev/reference/plot.mkinfit-5.png b/docs/dev/reference/plot.mkinfit-5.png index 1109c8df..b4b6528b 100644 Binary files a/docs/dev/reference/plot.mkinfit-5.png and b/docs/dev/reference/plot.mkinfit-5.png differ diff --git a/docs/dev/reference/plot.mkinfit-6.png b/docs/dev/reference/plot.mkinfit-6.png index 230c90e9..f71f1769 100644 Binary files a/docs/dev/reference/plot.mkinfit-6.png and b/docs/dev/reference/plot.mkinfit-6.png differ diff --git a/docs/dev/reference/plot.mkinfit-7.png b/docs/dev/reference/plot.mkinfit-7.png index b23427b5..98fee908 100644 Binary files a/docs/dev/reference/plot.mkinfit-7.png and b/docs/dev/reference/plot.mkinfit-7.png differ diff --git a/docs/dev/reference/plot.mkinfit.html b/docs/dev/reference/plot.mkinfit.html index ffbd1206..3a05a02d 100644 --- a/docs/dev/reference/plot.mkinfit.html +++ b/docs/dev/reference/plot.mkinfit.html @@ -74,7 +74,7 @@ observed data together with the solution of the fitted model." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -122,7 +122,7 @@ observed data together with the solution of the fitted model." />
    • - + @@ -141,7 +141,7 @@ observed data together with the solution of the fitted model." />

      Plot the observed data and the fitted model of an mkinfit object

      - Source: R/plot.mkinfit.R + Source: R/plot.mkinfit.R
      @@ -152,49 +152,49 @@ observed data together with the solution of the fitted model.

      # S3 method for mkinfit
-plot(
-  x,
-  fit = x,
-  obs_vars = names(fit$mkinmod$map),
-  xlab = "Time",
-  ylab = "Observed",
-  xlim = range(fit$data$time),
-  ylim = "default",
-  col_obs = 1:length(obs_vars),
-  pch_obs = col_obs,
-  lty_obs = rep(1, length(obs_vars)),
-  add = FALSE,
-  legend = !add,
-  show_residuals = FALSE,
-  show_errplot = FALSE,
-  maxabs = "auto",
-  sep_obs = FALSE,
-  rel.height.middle = 0.9,
-  row_layout = FALSE,
-  lpos = "topright",
-  inset = c(0.05, 0.05),
-  show_errmin = FALSE,
-  errmin_digits = 3,
-  frame = TRUE,
-  ...
-)
-
-plot_sep(
-  fit,
-  show_errmin = TRUE,
-  show_residuals = ifelse(identical(fit$err_mod, "const"), TRUE, "standardized"),
-  ...
-)
-
-plot_res(
-  fit,
-  sep_obs = FALSE,
-  show_errmin = sep_obs,
-  standardized = ifelse(identical(fit$err_mod, "const"), FALSE, TRUE),
-  ...
-)
-
-plot_err(fit, sep_obs = FALSE, show_errmin = sep_obs, ...)
      +plot( + x, + fit = x, + obs_vars = names(fit$mkinmod$map), + xlab = "Time", + ylab = "Observed", + xlim = range(fit$data$time), + ylim = "default", + col_obs = 1:length(obs_vars), + pch_obs = col_obs, + lty_obs = rep(1, length(obs_vars)), + add = FALSE, + legend = !add, + show_residuals = FALSE, + show_errplot = FALSE, + maxabs = "auto", + sep_obs = FALSE, + rel.height.middle = 0.9, + row_layout = FALSE, + lpos = "topright", + inset = c(0.05, 0.05), + show_errmin = FALSE, + errmin_digits = 3, + frame = TRUE, + ... +) + +plot_sep( + fit, + show_errmin = TRUE, + show_residuals = ifelse(identical(fit$err_mod, "const"), TRUE, "standardized"), + ... +) + +plot_res( + fit, + sep_obs = FALSE, + show_errmin = sep_obs, + standardized = ifelse(identical(fit$err_mod, "const"), FALSE, TRUE), + ... +) + +plot_err(fit, sep_obs = FALSE, show_errmin = sep_obs, ...)

      Arguments

    @@ -314,7 +314,7 @@ chi2 error percentage.

    - + @@ -331,22 +331,35 @@ standardized in the residual plot?

    If the current plot device is a tikz device, then latex is being used for the formatting of the chi2 error level, if show_errmin = TRUE.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
 # One parent compound, one metabolite, both single first order, path from
 # parent to sink included
 # \dontrun{
-SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
-                   m1 = mkinsub("SFO", full = "Metabolite M1" ))
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
    #> Warning: Observations with value of zero were removed from the data
    #> Warning: Shapiro-Wilk test for standardized residuals: p =  0.0165
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, error_model = "tc")
    #> Warning: Observations with value of zero were removed from the data
    plot(fit)
    plot_res(fit)
    plot_res(fit, standardized = FALSE)
    plot_err(fit)
    
+SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
+                   m1 = mkinsub("SFO", full = "Metabolite M1" ))
+
    #> Successfully compiled differential equation model from auto-generated C code.
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+
    #> Warning: Observations with value of zero were removed from the data
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, error_model = "tc")
+
    #> Warning: Observations with value of zero were removed from the data
    plot(fit)
+
    plot_res(fit)
+
    plot_res(fit, standardized = FALSE)
+
    plot_err(fit)
+
    
 # Show the observed variables separately, with residuals
-plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"),
-     show_errmin = TRUE)
    
+plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"),
+     show_errmin = TRUE)
+
    
 # The same can be obtained with less typing, using the convenience function plot_sep
-plot_sep(fit, lpos = c("topright", "bottomright"))
    
+plot_sep(fit, lpos = c("topright", "bottomright"))
+
    
 # Show the observed variables separately, with the error model
-plot(fit, sep_obs = TRUE, show_errplot = TRUE, lpos = c("topright", "bottomright"),
-     show_errmin = TRUE)
    # }
+plot(fit, sep_obs = TRUE, show_errplot = TRUE, lpos = c("topright", "bottomright"),
+     show_errmin = TRUE)
+
    # }
    @@ -364,7 +377,7 @@ latex is being used for the formatting of the chi2 error level, if
    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/plot.mmkin-1.png b/docs/dev/reference/plot.mmkin-1.png index 24fa6ca7..438d5a53 100644 Binary files a/docs/dev/reference/plot.mmkin-1.png and b/docs/dev/reference/plot.mmkin-1.png differ diff --git a/docs/dev/reference/plot.mmkin-2.png b/docs/dev/reference/plot.mmkin-2.png index 377e50b5..ee04b3c4 100644 Binary files a/docs/dev/reference/plot.mmkin-2.png and b/docs/dev/reference/plot.mmkin-2.png differ diff --git a/docs/dev/reference/plot.mmkin-3.png b/docs/dev/reference/plot.mmkin-3.png index 3ea7b38a..e06ed002 100644 Binary files a/docs/dev/reference/plot.mmkin-3.png and b/docs/dev/reference/plot.mmkin-3.png differ diff --git a/docs/dev/reference/plot.mmkin-4.png b/docs/dev/reference/plot.mmkin-4.png index 017fbd1d..5869df55 100644 Binary files a/docs/dev/reference/plot.mmkin-4.png and b/docs/dev/reference/plot.mmkin-4.png differ diff --git a/docs/dev/reference/plot.mmkin-5.png b/docs/dev/reference/plot.mmkin-5.png index e7463916..927c573b 100644 Binary files a/docs/dev/reference/plot.mmkin-5.png and b/docs/dev/reference/plot.mmkin-5.png differ diff --git a/docs/dev/reference/plot.mmkin.html b/docs/dev/reference/plot.mmkin.html index f02e2ea6..32da836d 100644 --- a/docs/dev/reference/plot.mmkin.html +++ b/docs/dev/reference/plot.mmkin.html @@ -76,7 +76,7 @@ the fit of at least one model to the same dataset is shown." /> mkin - 0.9.50.3 + 0.9.50.4 @@ -124,7 +124,7 @@ the fit of at least one model to the same dataset is shown." />
    • - + @@ -144,31 +144,31 @@ the fit of at least one model to the same dataset is shown." />

      Plot model fits (observed and fitted) and the residuals for a row or column of an mmkin object

      - Source: R/plot.mmkin.R + Source: R/plot.mmkin.R
      -

      When x is a row selected from an mmkin object ([.mmkin), the +

      When x is a row selected from an mmkin object ([.mmkin), the same model fitted for at least one dataset is shown. When it is a column, the fit of at least one model to the same dataset is shown.

      # S3 method for mmkin
-plot(
-  x,
-  main = "auto",
-  legends = 1,
-  resplot = c("time", "errmod"),
-  standardized = FALSE,
-  show_errmin = TRUE,
-  errmin_var = "All data",
-  errmin_digits = 3,
-  cex = 0.7,
-  rel.height.middle = 0.9,
-  ymax = "auto",
-  ...
-)
      +plot( + x, + main = "auto", + legends = 1, + resplot = c("time", "errmod"), + standardized = FALSE, + show_errmin = TRUE, + errmin_var = "All data", + errmin_digits = 3, + cex = 0.7, + rel.height.middle = 0.9, + ymax = "auto", + ... +)

      Arguments

    ...

    Further arguments passed to plot.

    Further arguments passed to plot.
    standardized
    @@ -240,21 +240,30 @@ than two rows of plots are shown.

    If the current plot device is a tikz device, then latex is being used for the formatting of the chi2 error level.

    +

    Author

    + +

    Johannes Ranke

    Examples

    
   # \dontrun{
   # Only use one core not to offend CRAN checks
-  fits <- mmkin(c("FOMC", "HS"),
-                list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles
-                cores = 1, quiet = TRUE, error_model = "tc")
    #> Warning: Optimisation did not converge:
-#> iteration limit reached without convergence (10)
      plot(fits[, "FOCUS C"])
      plot(fits["FOMC", ])
      plot(fits["FOMC", ], show_errmin = FALSE)
    
+  fits <- mmkin(c("FOMC", "HS"),
+                list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles
+                cores = 1, quiet = TRUE, error_model = "tc")
+
    #> Warning: Optimisation did not converge:
+#> iteration limit reached without convergence (10)
      plot(fits[, "FOCUS C"])
+
      plot(fits["FOMC", ])
+
      plot(fits["FOMC", ], show_errmin = FALSE)
+
    
   # We can also plot a single fit, if we like the way plot.mmkin works, but then the plot
   # height should be smaller than the plot width (this is not possible for the html pages
   # generated by pkgdown, as far as I know).
-  plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
    
+  plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
+
    
   # Show the error models
-  plot(fits["FOMC", ], resplot = "errmod")
      # }
+  plot(fits["FOMC", ], resplot = "errmod")
+
      # }
    @@ -272,7 +281,7 @@ latex is being used for the formatting of the chi2 error level.

    -

    Site built with pkgdown 1.5.1.

    +

    Site built with pkgdown 1.6.1.

    diff --git a/docs/dev/reference/saem-5.png b/docs/dev/reference/saem-5.png index 6e6e0f91..a12f8383 100644 Binary files a/docs/dev/reference/saem-5.png and b/docs/dev/reference/saem-5.png differ diff --git a/docs/dev/reference/saem-6.png b/docs/dev/reference/saem-6.png new file mode 100644 index 00000000..314f9cd9 Binary files /dev/null and b/docs/dev/reference/saem-6.png differ diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index d0c3495a..948e1378 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -247,27 +247,27 @@ using mmkin.

    state.ini =c(parent =100), fixed_initials ="parent", quiet =TRUE)f_saem_p0_fixed<-saem(f_mmkin_parent_p0_fixed)
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:47:58 2020" +#> [1] "Thu Nov 19 14:51:31 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:00 2020"
    +#> [1] "Thu Nov 19 14:51:33 2020"
    f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE) f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:01 2020" +#> [1] "Thu Nov 19 14:51:34 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:03 2020"
    f_saem_fomc <- saem(f_mmkin_parent["FOMC", ]) +#> [1] "Thu Nov 19 14:51:36 2020"
    f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:03 2020" +#> [1] "Thu Nov 19 14:51:36 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:05 2020"
    f_saem_dfop <- saem(f_mmkin_parent["DFOP", ]) +#> [1] "Thu Nov 19 14:51:38 2020"
    f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:06 2020" +#> [1] "Thu Nov 19 14:51:39 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:08 2020"
    +#> [1] "Thu Nov 19 14:51:42 2020"
    # The returned saem.mmkin object contains an SaemixObject, therefore we can use # functions from saemix library(saemix) @@ -313,10 +313,10 @@ using mmkin.

    f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc") f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:11 2020" +#> [1] "Thu Nov 19 14:51:44 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:16 2020"
    compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so)) +#> [1] "Thu Nov 19 14:51:49 2020"
    compare.saemix(list(f_saem_fomc$so, f_saem_fomc_tc$so))
    #> Likelihoods computed by importance sampling
    #> AIC BIC #> 1 467.7096 464.9757 #> 2 469.5208 466.3963
    @@ -327,7 +327,7 @@ using mmkin.

    #> Successfully compiled differential equation model from auto-generated C code.
    dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"), A1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # The following fit uses analytical solutions for SFO-SFO and DFOP-SFO, -# and compiled ODEs for FOMC, both are fast +# and compiled ODEs for FOMC that are much slower f_mmkin <- mmkin(list( "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo), ds, quiet = TRUE) @@ -336,15 +336,15 @@ using mmkin.

    # solutions written for mkin this took around four minutes f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:18 2020" +#> [1] "Thu Nov 19 14:51:52 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:23 2020"
    f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ]) +#> [1] "Thu Nov 19 14:51:57 2020"
    f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ])
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:23 2020" +#> [1] "Thu Nov 19 14:51:57 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:32 2020"
    # We can use print, plot and summary methods to check the results +#> [1] "Thu Nov 19 14:52:06 2020"
    # We can use print, plot and summary methods to check the results print(f_saem_dfop_sfo)
    #> Kinetic nonlinear mixed-effects model fit by SAEM #> Structural model: @@ -359,8 +359,6 @@ using mmkin.

    #> 170 observations of 2 variable(s) grouped in 5 datasets #> #> Likelihood computed by importance sampling -#> -#> LL by is "-407.78 (df=13)" #> AIC BIC logLik #> 841.6 836.5 -407.8 #> @@ -385,13 +383,12 @@ using mmkin.

    #> SD.log_k1 1.42027 0.52714 2.3134 #> SD.log_k2 1.90634 0.70934 3.1033 #> SD.g_qlogis 0.44771 -0.86417 1.7596
    plot(f_saem_dfop_sfo) -
    summary(f_saem_dfop_sfo, data = FALSE) -
    #> -#> LL by is "-407.78 (df=13)"
    #> saemix version used for fitting: 3.1.9000 +
    summary(f_saem_dfop_sfo, data = TRUE) +
    #> saemix version used for fitting: 3.1.9000 #> mkin version used for pre-fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Wed Nov 11 19:48:33 2020 -#> Date of summary: Wed Nov 11 19:48:33 2020 +#> Date of fit: Thu Nov 19 14:52:07 2020 +#> Date of summary: Thu Nov 19 14:52:07 2020 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -406,7 +403,7 @@ using mmkin.

    #> #> Model predictions using solution type analytical #> -#> Fitted in 9.564 s using 300, 100 iterations +#> Fitted in 10.034 s using 300, 100 iterations #> #> Variance model: Constant variance #> @@ -472,11 +469,206 @@ using mmkin.

    #> Estimated disappearance times: #> DT50 DT90 DT50back DT50_k1 DT50_k2 #> parent 14.11 59.53 17.92 8.717 25.03 -#> A1 319.21 1060.38 NA NA NA
    +#> A1 319.21 1060.38 NA NA NA +#> +#> Data: +#> ds name time observed predicted residual std standardized +#> Dataset 6 parent 0 97.2 95.79523 -1.40477 1.883 -0.745888 +#> Dataset 6 parent 0 96.4 95.79523 -0.60477 1.883 -0.321114 +#> Dataset 6 parent 3 71.1 71.32042 0.22042 1.883 0.117035 +#> Dataset 6 parent 3 69.2 71.32042 2.12042 1.883 1.125873 +#> Dataset 6 parent 6 58.1 56.45256 -1.64744 1.883 -0.874739 +#> Dataset 6 parent 6 56.6 56.45256 -0.14744 1.883 -0.078288 +#> Dataset 6 parent 10 44.4 44.48523 0.08523 1.883 0.045256 +#> Dataset 6 parent 10 43.4 44.48523 1.08523 1.883 0.576224 +#> Dataset 6 parent 20 33.3 29.75774 -3.54226 1.883 -1.880826 +#> Dataset 6 parent 20 29.2 29.75774 0.55774 1.883 0.296141 +#> Dataset 6 parent 34 17.6 19.35710 1.75710 1.883 0.932966 +#> Dataset 6 parent 34 18.0 19.35710 1.35710 1.883 0.720578 +#> Dataset 6 parent 55 10.5 10.48443 -0.01557 1.883 -0.008266 +#> Dataset 6 parent 55 9.3 10.48443 1.18443 1.883 0.628895 +#> Dataset 6 parent 90 4.5 3.78622 -0.71378 1.883 -0.378995 +#> Dataset 6 parent 90 4.7 3.78622 -0.91378 1.883 -0.485188 +#> Dataset 6 parent 112 3.0 1.99608 -1.00392 1.883 -0.533048 +#> Dataset 6 parent 112 3.4 1.99608 -1.40392 1.883 -0.745435 +#> Dataset 6 parent 132 2.3 1.11539 -1.18461 1.883 -0.628990 +#> Dataset 6 parent 132 2.7 1.11539 -1.58461 1.883 -0.841377 +#> Dataset 6 A1 3 4.3 4.66132 0.36132 1.883 0.191849 +#> Dataset 6 A1 3 4.6 4.66132 0.06132 1.883 0.032559 +#> Dataset 6 A1 6 7.0 7.41087 0.41087 1.883 0.218157 +#> Dataset 6 A1 6 7.2 7.41087 0.21087 1.883 0.111964 +#> Dataset 6 A1 10 8.2 9.50878 1.30878 1.883 0.694921 +#> Dataset 6 A1 10 8.0 9.50878 1.50878 1.883 0.801114 +#> Dataset 6 A1 20 11.0 11.69902 0.69902 1.883 0.371157 +#> Dataset 6 A1 20 13.7 11.69902 -2.00098 1.883 -1.062455 +#> Dataset 6 A1 34 11.5 12.67784 1.17784 1.883 0.625396 +#> Dataset 6 A1 34 12.7 12.67784 -0.02216 1.883 -0.011765 +#> Dataset 6 A1 55 14.9 12.78556 -2.11444 1.883 -1.122701 +#> Dataset 6 A1 55 14.5 12.78556 -1.71444 1.883 -0.910314 +#> Dataset 6 A1 90 12.1 11.52954 -0.57046 1.883 -0.302898 +#> Dataset 6 A1 90 12.3 11.52954 -0.77046 1.883 -0.409092 +#> Dataset 6 A1 112 9.9 10.43825 0.53825 1.883 0.285793 +#> Dataset 6 A1 112 10.2 10.43825 0.23825 1.883 0.126503 +#> Dataset 6 A1 132 8.8 9.42830 0.62830 1.883 0.333609 +#> Dataset 6 A1 132 7.8 9.42830 1.62830 1.883 0.864577 +#> Dataset 7 parent 0 93.6 90.91477 -2.68523 1.883 -1.425772 +#> Dataset 7 parent 0 92.3 90.91477 -1.38523 1.883 -0.735514 +#> Dataset 7 parent 3 87.0 84.76874 -2.23126 1.883 -1.184726 +#> Dataset 7 parent 3 82.2 84.76874 2.56874 1.883 1.363919 +#> Dataset 7 parent 7 74.0 77.62735 3.62735 1.883 1.926003 +#> Dataset 7 parent 7 73.9 77.62735 3.72735 1.883 1.979100 +#> Dataset 7 parent 14 64.2 67.52266 3.32266 1.883 1.764224 +#> Dataset 7 parent 14 69.5 67.52266 -1.97734 1.883 -1.049904 +#> Dataset 7 parent 30 54.0 52.41949 -1.58051 1.883 -0.839202 +#> Dataset 7 parent 30 54.6 52.41949 -2.18051 1.883 -1.157783 +#> Dataset 7 parent 60 41.1 39.36582 -1.73418 1.883 -0.920794 +#> Dataset 7 parent 60 38.4 39.36582 0.96582 1.883 0.512818 +#> Dataset 7 parent 90 32.5 33.75388 1.25388 1.883 0.665771 +#> Dataset 7 parent 90 35.5 33.75388 -1.74612 1.883 -0.927132 +#> Dataset 7 parent 120 28.1 30.41716 2.31716 1.883 1.230335 +#> Dataset 7 parent 120 29.0 30.41716 1.41716 1.883 0.752464 +#> Dataset 7 parent 180 26.5 25.66046 -0.83954 1.883 -0.445767 +#> Dataset 7 parent 180 27.6 25.66046 -1.93954 1.883 -1.029832 +#> Dataset 7 A1 3 3.9 2.69355 -1.20645 1.883 -0.640585 +#> Dataset 7 A1 3 3.1 2.69355 -0.40645 1.883 -0.215811 +#> Dataset 7 A1 7 6.9 5.81807 -1.08193 1.883 -0.574470 +#> Dataset 7 A1 7 6.6 5.81807 -0.78193 1.883 -0.415180 +#> Dataset 7 A1 14 10.4 10.22529 -0.17471 1.883 -0.092767 +#> Dataset 7 A1 14 8.3 10.22529 1.92529 1.883 1.022265 +#> Dataset 7 A1 30 14.4 16.75484 2.35484 1.883 1.250345 +#> Dataset 7 A1 30 13.7 16.75484 3.05484 1.883 1.622022 +#> Dataset 7 A1 60 22.1 22.22540 0.12540 1.883 0.066583 +#> Dataset 7 A1 60 22.3 22.22540 -0.07460 1.883 -0.039610 +#> Dataset 7 A1 90 27.5 24.38799 -3.11201 1.883 -1.652376 +#> Dataset 7 A1 90 25.4 24.38799 -1.01201 1.883 -0.537344 +#> Dataset 7 A1 120 28.0 25.53294 -2.46706 1.883 -1.309927 +#> Dataset 7 A1 120 26.6 25.53294 -1.06706 1.883 -0.566572 +#> Dataset 7 A1 180 25.8 26.94943 1.14943 1.883 0.610309 +#> Dataset 7 A1 180 25.3 26.94943 1.64943 1.883 0.875793 +#> Dataset 8 parent 0 91.9 91.53246 -0.36754 1.883 -0.195151 +#> Dataset 8 parent 0 90.8 91.53246 0.73246 1.883 0.388914 +#> Dataset 8 parent 1 64.9 67.73197 2.83197 1.883 1.503686 +#> Dataset 8 parent 1 66.2 67.73197 1.53197 1.883 0.813428 +#> Dataset 8 parent 3 43.5 41.58448 -1.91552 1.883 -1.017081 +#> Dataset 8 parent 3 44.1 41.58448 -2.51552 1.883 -1.335661 +#> Dataset 8 parent 8 18.3 19.62286 1.32286 1.883 0.702395 +#> Dataset 8 parent 8 18.1 19.62286 1.52286 1.883 0.808589 +#> Dataset 8 parent 14 10.2 10.77819 0.57819 1.883 0.306999 +#> Dataset 8 parent 14 10.8 10.77819 -0.02181 1.883 -0.011582 +#> Dataset 8 parent 27 4.9 3.26977 -1.63023 1.883 -0.865599 +#> Dataset 8 parent 27 3.3 3.26977 -0.03023 1.883 -0.016051 +#> Dataset 8 parent 48 1.6 0.48024 -1.11976 1.883 -0.594557 +#> Dataset 8 parent 48 1.5 0.48024 -1.01976 1.883 -0.541460 +#> Dataset 8 parent 70 1.1 0.06438 -1.03562 1.883 -0.549881 +#> Dataset 8 parent 70 0.9 0.06438 -0.83562 1.883 -0.443688 +#> Dataset 8 A1 1 9.6 7.61539 -1.98461 1.883 -1.053761 +#> Dataset 8 A1 1 7.7 7.61539 -0.08461 1.883 -0.044923 +#> Dataset 8 A1 3 15.0 15.47954 0.47954 1.883 0.254622 +#> Dataset 8 A1 3 15.1 15.47954 0.37954 1.883 0.201525 +#> Dataset 8 A1 8 21.2 20.22616 -0.97384 1.883 -0.517076 +#> Dataset 8 A1 8 21.1 20.22616 -0.87384 1.883 -0.463979 +#> Dataset 8 A1 14 19.7 20.00067 0.30067 1.883 0.159645 +#> Dataset 8 A1 14 18.9 20.00067 1.10067 1.883 0.584419 +#> Dataset 8 A1 27 17.5 16.38142 -1.11858 1.883 -0.593929 +#> Dataset 8 A1 27 15.9 16.38142 0.48142 1.883 0.255619 +#> Dataset 8 A1 48 9.5 10.25357 0.75357 1.883 0.400123 +#> Dataset 8 A1 48 9.8 10.25357 0.45357 1.883 0.240833 +#> Dataset 8 A1 70 6.2 5.95728 -0.24272 1.883 -0.128878 +#> Dataset 8 A1 70 6.1 5.95728 -0.14272 1.883 -0.075781 +#> Dataset 9 parent 0 99.8 97.47274 -2.32726 1.883 -1.235697 +#> Dataset 9 parent 0 98.3 97.47274 -0.82726 1.883 -0.439246 +#> Dataset 9 parent 1 77.1 79.72257 2.62257 1.883 1.392500 +#> Dataset 9 parent 1 77.2 79.72257 2.52257 1.883 1.339404 +#> Dataset 9 parent 3 59.0 56.26497 -2.73503 1.883 -1.452212 +#> Dataset 9 parent 3 58.1 56.26497 -1.83503 1.883 -0.974342 +#> Dataset 9 parent 8 27.4 31.66985 4.26985 1.883 2.267151 +#> Dataset 9 parent 8 29.2 31.66985 2.46985 1.883 1.311410 +#> Dataset 9 parent 14 19.1 22.39789 3.29789 1.883 1.751071 +#> Dataset 9 parent 14 29.6 22.39789 -7.20211 1.883 -3.824090 +#> Dataset 9 parent 27 10.1 14.21758 4.11758 1.883 2.186301 +#> Dataset 9 parent 27 18.2 14.21758 -3.98242 1.883 -2.114537 +#> Dataset 9 parent 48 4.5 7.27921 2.77921 1.883 1.475671 +#> Dataset 9 parent 48 9.1 7.27921 -1.82079 1.883 -0.966780 +#> Dataset 9 parent 70 2.3 3.61470 1.31470 1.883 0.698065 +#> Dataset 9 parent 70 2.9 3.61470 0.71470 1.883 0.379485 +#> Dataset 9 parent 91 2.0 1.85303 -0.14697 1.883 -0.078038 +#> Dataset 9 parent 91 1.8 1.85303 0.05303 1.883 0.028155 +#> Dataset 9 parent 120 2.0 0.73645 -1.26355 1.883 -0.670906 +#> Dataset 9 parent 120 2.2 0.73645 -1.46355 1.883 -0.777099 +#> Dataset 9 A1 1 4.2 3.87843 -0.32157 1.883 -0.170743 +#> Dataset 9 A1 1 3.9 3.87843 -0.02157 1.883 -0.011453 +#> Dataset 9 A1 3 7.4 8.90535 1.50535 1.883 0.799291 +#> Dataset 9 A1 3 7.9 8.90535 1.00535 1.883 0.533807 +#> Dataset 9 A1 8 14.5 13.75172 -0.74828 1.883 -0.397312 +#> Dataset 9 A1 8 13.7 13.75172 0.05172 1.883 0.027462 +#> Dataset 9 A1 14 14.2 14.97541 0.77541 1.883 0.411715 +#> Dataset 9 A1 14 12.2 14.97541 2.77541 1.883 1.473650 +#> Dataset 9 A1 27 13.7 14.94728 1.24728 1.883 0.662266 +#> Dataset 9 A1 27 13.2 14.94728 1.74728 1.883 0.927750 +#> Dataset 9 A1 48 13.6 13.66078 0.06078 1.883 0.032272 +#> Dataset 9 A1 48 15.4 13.66078 -1.73922 1.883 -0.923470 +#> Dataset 9 A1 70 10.4 11.84899 1.44899 1.883 0.769365 +#> Dataset 9 A1 70 11.6 11.84899 0.24899 1.883 0.132204 +#> Dataset 9 A1 91 10.0 10.09177 0.09177 1.883 0.048727 +#> Dataset 9 A1 91 9.5 10.09177 0.59177 1.883 0.314211 +#> Dataset 9 A1 120 9.1 7.91379 -1.18621 1.883 -0.629841 +#> Dataset 9 A1 120 9.0 7.91379 -1.08621 1.883 -0.576745 +#> Dataset 10 parent 0 96.1 93.65257 -2.44743 1.883 -1.299505 +#> Dataset 10 parent 0 94.3 93.65257 -0.64743 1.883 -0.343763 +#> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 +#> Dataset 10 parent 8 73.9 77.85906 3.95906 1.883 2.102132 +#> Dataset 10 parent 14 69.4 70.17143 0.77143 1.883 0.409606 +#> Dataset 10 parent 14 73.1 70.17143 -2.92857 1.883 -1.554974 +#> Dataset 10 parent 21 65.6 63.99188 -1.60812 1.883 -0.853862 +#> Dataset 10 parent 21 65.3 63.99188 -1.30812 1.883 -0.694572 +#> Dataset 10 parent 41 55.9 54.64292 -1.25708 1.883 -0.667467 +#> Dataset 10 parent 41 54.4 54.64292 0.24292 1.883 0.128985 +#> Dataset 10 parent 63 47.0 49.61303 2.61303 1.883 1.387433 +#> Dataset 10 parent 63 49.3 49.61303 0.31303 1.883 0.166207 +#> Dataset 10 parent 91 44.7 45.17807 0.47807 1.883 0.253839 +#> Dataset 10 parent 91 46.7 45.17807 -1.52193 1.883 -0.808096 +#> Dataset 10 parent 120 42.1 41.27970 -0.82030 1.883 -0.435552 +#> Dataset 10 parent 120 41.3 41.27970 -0.02030 1.883 -0.010778 +#> Dataset 10 A1 8 3.3 3.99294 0.69294 1.883 0.367929 +#> Dataset 10 A1 8 3.4 3.99294 0.59294 1.883 0.314832 +#> Dataset 10 A1 14 3.9 5.92756 2.02756 1.883 1.076570 +#> Dataset 10 A1 14 2.9 5.92756 3.02756 1.883 1.607538 +#> Dataset 10 A1 21 6.4 7.47313 1.07313 1.883 0.569799 +#> Dataset 10 A1 21 7.2 7.47313 0.27313 1.883 0.145025 +#> Dataset 10 A1 41 9.1 9.76819 0.66819 1.883 0.354786 +#> Dataset 10 A1 41 8.5 9.76819 1.26819 1.883 0.673367 +#> Dataset 10 A1 63 11.7 10.94733 -0.75267 1.883 -0.399643 +#> Dataset 10 A1 63 12.0 10.94733 -1.05267 1.883 -0.558933 +#> Dataset 10 A1 91 13.3 11.93773 -1.36227 1.883 -0.723321 +#> Dataset 10 A1 91 13.2 11.93773 -1.26227 1.883 -0.670224 +#> Dataset 10 A1 120 14.3 12.77666 -1.52334 1.883 -0.808847 +#> Dataset 10 A1 120 12.1 12.77666 0.67666 1.883 0.359282
    # Using a single core, the following takes about 6 minutes as we do not have an # analytical solution. Using 10 cores it is slower instead of faster -#f_saem_fomc <- saem(f_mmkin["FOMC-SFO", ], cores = 1) -# } +f_saem_fomc <- saem(f_mmkin["FOMC-SFO", ], cores = 1) +
    #> Running main SAEM algorithm +#> [1] "Thu Nov 19 14:52:08 2020" +#> DLSODA- At current T (=R1), MXSTEP (=I1) steps +#> taken on this call before reaching TOUT +#> In above message, I1 = 5000 +#> +#> In above message, R1 = 0.00156238 +#> +#> DLSODA- At T (=R1) and step size H (=R2), the +#> corrector convergence failed repeatedly +#> or with ABS(H) = HMIN +#> In above message, R1 = 0, R2 = 1.1373e-10 +#> +#> DLSODA- At current T (=R1), MXSTEP (=I1) steps +#> taken on this call before reaching TOUT +#> In above message, I1 = 5000 +#> +#> In above message, R1 = 2.24752e-06 +#> +#> .... +#> Minimisation finished +#> [1] "Thu Nov 19 14:59:05 2020"
    plot(f_saem_fomc) +
    # }
    #> mkin version used for fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Sat Nov 7 13:28:04 2020 -#> Date of summary: Sat Nov 7 13:28:04 2020 +#> Date of fit: Thu Nov 19 14:59:41 2020 +#> Date of summary: Thu Nov 19 14:59:41 2020 #> #> Equations: #> d_parent/dt = - k_parent * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 131 model solutions performed in 0.028 s +#> Fitted using 131 model solutions performed in 0.033 s #> #> Error model: Constant variance #> diff --git a/docs/dev/reference/summary.nlme.mmkin.html b/docs/dev/reference/summary.nlme.mmkin.html index d35e8713..d016796e 100644 --- a/docs/dev/reference/summary.nlme.mmkin.html +++ b/docs/dev/reference/summary.nlme.mmkin.html @@ -265,8 +265,8 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> nlme version used for fitting: 3.1.150.1 #> mkin version used for pre-fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Sat Nov 7 13:28:06 2020 -#> Date of summary: Sat Nov 7 13:28:06 2020 +#> Date of fit: Thu Nov 19 14:59:43 2020 +#> Date of summary: Thu Nov 19 14:59:43 2020 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -276,7 +276,7 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> #> Model predictions using solution type analytical #> -#> Fitted in 0.588 s using 5 iterations +#> Fitted in 0.681 s using 5 iterations #> #> Variance model: Two-component variance function #> @@ -293,24 +293,20 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> 555.792 570.7908 -271.896 #> #> Optimised, transformed parameters with symmetric confidence intervals: -#> lower est. upper -#> parent_0 94.701336 97.763446 100.82556 -#> log_k_parent -5.007574 -4.461767 -3.91596 +#> lower est. upper +#> parent_0 94.701 97.763 100.826 +#> log_k_parent -5.008 -4.462 -3.916 #> #> Correlation: #> prnt_0 #> log_k_parent 0.024 #> -#> Backtransformed parameters with asymmetric confidence intervals: -#> lower est. upper -#> parent_0 94.701335804 97.76344625 100.82555670 -#> k_parent 0.006687109 0.01154195 0.01992142 #> Random effects: #> Formula: list(parent_0 ~ 1, log_k_parent ~ 1) #> Level: ds #> Structure: Diagonal #> parent_0 log_k_parent Residual -#> StdDev: 16.65969 3.516961 5.709013 +#> StdDev: 2.898 0.6119 1 #> #> Variance function: #> Structure: Constant plus proportion of variance covariate @@ -319,6 +315,11 @@ José Pinheiro and Douglas Bates for the components inherited from nlme

    #> const prop #> 1.55075176 0.05680853 #> +#> Backtransformed parameters with asymmetric confidence intervals: +#> lower est. upper +#> parent_0 94.701336 97.76345 100.82556 +#> k_parent 0.006687 0.01154 0.01992 +#> #> Estimated disappearance times: #> DT50 DT90 #> parent 60.05 199.5 diff --git a/docs/dev/reference/summary.saem.mmkin.html b/docs/dev/reference/summary.saem.mmkin.html index 8a5d001a..b7804247 100644 --- a/docs/dev/reference/summary.saem.mmkin.html +++ b/docs/dev/reference/summary.saem.mmkin.html @@ -260,16 +260,15 @@ saemix authors for the parts inherited from saemix.

    quiet = TRUE, error_model = "tc", cores = 5) f_saem_dfop_sfo <- saem(f_mmkin_dfop_sfo)
    #> Running main SAEM algorithm -#> [1] "Wed Nov 11 19:48:36 2020" +#> [1] "Thu Nov 19 14:59:46 2020" #> .... #> Minimisation finished -#> [1] "Wed Nov 11 19:48:48 2020"
    summary(f_saem_dfop_sfo, data = TRUE) -
    #> -#> LL by is "-401.01 (df=14)"
    #> saemix version used for fitting: 3.1.9000 +#> [1] "Thu Nov 19 15:00:00 2020"
    summary(f_saem_dfop_sfo, data = TRUE) +
    #> saemix version used for fitting: 3.1.9000 #> mkin version used for pre-fitting: 0.9.50.4 #> R version used for fitting: 4.0.3 -#> Date of fit: Wed Nov 11 19:48:49 2020 -#> Date of summary: Wed Nov 11 19:48:49 2020 +#> Date of fit: Thu Nov 19 15:00:01 2020 +#> Date of summary: Thu Nov 19 15:00:01 2020 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -284,7 +283,7 @@ saemix authors for the parts inherited from saemix.

    #> #> Model predictions using solution type analytical #> -#> Fitted in 13.272 s using 300, 100 iterations +#> Fitted in 15.23 s using 300, 100 iterations #> #> Variance model: Two-component variance function #> @@ -354,178 +353,178 @@ saemix authors for the parts inherited from saemix.

    #> m1 40.60 134.88 NA NA NA #> #> Data: -#> ds name time observed predicted residual standardized -#> ds 1 parent 0 89.8 9.869e+01 -8.894553 1.273163 -#> ds 1 parent 0 104.1 9.869e+01 5.405447 -0.773734 -#> ds 1 parent 1 88.7 9.413e+01 -5.426448 0.810727 -#> ds 1 parent 1 95.5 9.413e+01 1.373552 -0.205213 -#> ds 1 parent 3 81.8 8.576e+01 -3.961821 0.643463 -#> ds 1 parent 3 94.5 8.576e+01 8.738179 -1.419220 -#> ds 1 parent 7 71.5 7.168e+01 -0.184828 0.035175 -#> ds 1 parent 7 70.3 7.168e+01 -1.384828 0.263550 -#> ds 1 parent 14 54.2 5.351e+01 0.688235 -0.168298 -#> ds 1 parent 14 49.6 5.351e+01 -3.911765 0.956565 -#> ds 1 parent 28 31.5 3.209e+01 -0.590445 0.217395 -#> ds 1 parent 28 28.8 3.209e+01 -3.290445 1.211502 -#> ds 1 parent 60 12.1 1.272e+01 -0.618158 0.419377 -#> ds 1 parent 60 13.6 1.272e+01 0.881842 -0.598269 -#> ds 1 parent 90 6.2 6.085e+00 0.115212 -0.109861 -#> ds 1 parent 90 8.3 6.085e+00 2.215212 -2.112329 -#> ds 1 parent 120 2.2 3.009e+00 -0.809439 0.950563 -#> ds 1 parent 120 2.4 3.009e+00 -0.609439 0.715693 -#> ds 1 m1 1 0.3 1.129e+00 -0.828817 1.133869 -#> ds 1 m1 1 0.2 1.129e+00 -0.928817 1.270675 -#> ds 1 m1 3 2.2 3.141e+00 -0.940880 1.094093 -#> ds 1 m1 3 3.0 3.141e+00 -0.140880 0.163821 -#> ds 1 m1 7 6.5 6.326e+00 0.174162 -0.163662 -#> ds 1 m1 7 5.0 6.326e+00 -1.325838 1.245901 -#> ds 1 m1 14 10.2 9.883e+00 0.317417 -0.245642 -#> ds 1 m1 14 9.5 9.883e+00 -0.382583 0.296072 -#> ds 1 m1 28 12.2 1.251e+01 -0.309856 0.212138 -#> ds 1 m1 28 13.4 1.251e+01 0.890144 -0.609422 -#> ds 1 m1 60 11.8 1.086e+01 0.940009 -0.693807 -#> ds 1 m1 60 13.2 1.086e+01 2.340009 -1.727126 -#> ds 1 m1 90 6.6 7.823e+00 -1.222977 1.054158 -#> ds 1 m1 90 9.3 7.823e+00 1.477023 -1.273135 -#> ds 1 m1 120 3.5 5.315e+00 -1.815201 1.816354 -#> ds 1 m1 120 5.4 5.315e+00 0.084799 -0.084853 -#> ds 2 parent 0 118.0 1.031e+02 14.876736 -2.046284 -#> ds 2 parent 0 99.8 1.031e+02 -3.323264 0.457112 -#> ds 2 parent 1 90.2 9.757e+01 -7.371379 1.066126 -#> ds 2 parent 1 94.6 9.757e+01 -2.971379 0.429752 -#> ds 2 parent 3 96.1 8.788e+01 8.222746 -1.306721 -#> ds 2 parent 3 78.4 8.788e+01 -9.477254 1.506081 -#> ds 2 parent 7 77.9 7.293e+01 4.972272 -0.932149 -#> ds 2 parent 7 77.7 7.293e+01 4.772272 -0.894656 -#> ds 2 parent 14 56.0 5.602e+01 -0.016773 0.003947 -#> ds 2 parent 14 54.7 5.602e+01 -1.316773 0.309830 -#> ds 2 parent 28 36.6 3.855e+01 -1.945779 0.621680 -#> ds 2 parent 28 36.8 3.855e+01 -1.745779 0.557779 -#> ds 2 parent 60 22.1 2.101e+01 1.086693 -0.541771 -#> ds 2 parent 60 24.7 2.101e+01 3.686693 -1.838002 -#> ds 2 parent 90 12.4 1.246e+01 -0.058759 0.040319 -#> ds 2 parent 90 10.8 1.246e+01 -1.658759 1.138195 -#> ds 2 parent 120 6.8 7.406e+00 -0.606226 0.534861 -#> ds 2 parent 120 7.9 7.406e+00 0.493774 -0.435647 -#> ds 2 m1 1 1.3 1.438e+00 -0.138236 0.184118 -#> ds 2 m1 3 3.7 3.879e+00 -0.178617 0.196874 -#> ds 2 m1 3 4.7 3.879e+00 0.821383 -0.905344 -#> ds 2 m1 7 8.1 7.389e+00 0.710951 -0.627868 -#> ds 2 m1 7 7.9 7.389e+00 0.510951 -0.451240 -#> ds 2 m1 14 10.1 1.069e+01 -0.593533 0.441556 -#> ds 2 m1 14 10.3 1.069e+01 -0.393533 0.292767 -#> ds 2 m1 28 10.7 1.240e+01 -1.703647 1.171837 -#> ds 2 m1 28 12.2 1.240e+01 -0.203647 0.140077 -#> ds 2 m1 60 10.7 1.055e+01 0.147672 -0.110605 -#> ds 2 m1 60 12.5 1.055e+01 1.947672 -1.458786 -#> ds 2 m1 90 9.1 8.010e+00 1.090041 -0.929963 -#> ds 2 m1 90 7.4 8.010e+00 -0.609959 0.520383 -#> ds 2 m1 120 6.1 5.793e+00 0.306797 -0.297858 -#> ds 2 m1 120 4.5 5.793e+00 -1.293203 1.255523 -#> ds 3 parent 0 106.2 1.035e+02 2.712344 -0.371886 -#> ds 3 parent 0 106.9 1.035e+02 3.412344 -0.467862 -#> ds 3 parent 1 107.4 9.548e+01 11.924044 -1.758752 -#> ds 3 parent 1 96.1 9.548e+01 0.624044 -0.092044 -#> ds 3 parent 3 79.4 8.246e+01 -3.056105 0.514055 -#> ds 3 parent 3 82.6 8.246e+01 0.143895 -0.024204 -#> ds 3 parent 7 63.9 6.489e+01 -0.991141 0.205676 -#> ds 3 parent 7 62.4 6.489e+01 -2.491141 0.516947 -#> ds 3 parent 14 51.0 4.869e+01 2.306824 -0.610198 -#> ds 3 parent 14 47.1 4.869e+01 -1.593176 0.421425 -#> ds 3 parent 28 36.1 3.480e+01 1.304261 -0.451388 -#> ds 3 parent 28 36.6 3.480e+01 1.804261 -0.624431 -#> ds 3 parent 60 20.1 1.988e+01 0.221952 -0.114821 -#> ds 3 parent 60 19.8 1.988e+01 -0.078048 0.040376 -#> ds 3 parent 90 11.3 1.194e+01 -0.642458 0.451083 -#> ds 3 parent 90 10.7 1.194e+01 -1.242458 0.872355 -#> ds 3 parent 120 8.2 7.176e+00 1.023847 -0.915231 -#> ds 3 parent 120 7.3 7.176e+00 0.123847 -0.110709 -#> ds 3 m1 0 0.8 8.527e-13 0.800000 -1.214712 -#> ds 3 m1 1 1.8 1.856e+00 -0.055925 0.071921 -#> ds 3 m1 1 2.3 1.856e+00 0.444075 -0.571099 -#> ds 3 m1 3 4.2 4.780e+00 -0.580164 0.601168 -#> ds 3 m1 3 4.1 4.780e+00 -0.680164 0.704788 -#> ds 3 m1 7 6.8 8.410e+00 -1.609920 1.344090 -#> ds 3 m1 7 10.1 8.410e+00 1.690080 -1.411014 -#> ds 3 m1 14 11.4 1.098e+01 0.424444 -0.311572 -#> ds 3 m1 14 12.8 1.098e+01 1.824444 -1.339271 -#> ds 3 m1 28 11.5 1.142e+01 0.079336 -0.057043 -#> ds 3 m1 28 10.6 1.142e+01 -0.820664 0.590065 -#> ds 3 m1 60 7.5 9.110e+00 -1.610231 1.295778 -#> ds 3 m1 60 8.6 9.110e+00 -0.510231 0.410591 -#> ds 3 m1 90 7.3 6.799e+00 0.501085 -0.457825 -#> ds 3 m1 90 8.1 6.799e+00 1.301085 -1.188759 -#> ds 3 m1 120 5.3 4.868e+00 0.431505 -0.444518 -#> ds 3 m1 120 3.8 4.868e+00 -1.068495 1.100718 -#> ds 4 parent 0 104.7 9.926e+01 5.444622 -0.775351 -#> ds 4 parent 0 88.3 9.926e+01 -10.955378 1.560119 -#> ds 4 parent 1 94.2 9.618e+01 -1.978413 0.289883 -#> ds 4 parent 1 94.6 9.618e+01 -1.578413 0.231274 -#> ds 4 parent 3 78.1 9.037e+01 -12.268550 1.901399 -#> ds 4 parent 3 96.5 9.037e+01 6.131450 -0.950262 -#> ds 4 parent 7 76.2 7.999e+01 -3.794958 0.655739 -#> ds 4 parent 7 77.8 7.999e+01 -2.194958 0.379272 -#> ds 4 parent 14 70.8 6.518e+01 5.624996 -1.162874 -#> ds 4 parent 14 67.3 6.518e+01 2.124996 -0.439307 -#> ds 4 parent 28 43.1 4.462e+01 -1.517860 0.431312 -#> ds 4 parent 28 45.1 4.462e+01 0.482140 -0.137004 -#> ds 4 parent 60 21.3 2.130e+01 0.003305 -0.001633 -#> ds 4 parent 60 23.5 2.130e+01 2.203305 -1.088598 -#> ds 4 parent 90 11.8 1.180e+01 -0.002834 0.002002 -#> ds 4 parent 90 12.1 1.180e+01 0.297166 -0.209966 -#> ds 4 parent 120 7.0 6.868e+00 0.132251 -0.120348 -#> ds 4 parent 120 6.2 6.868e+00 -0.667749 0.607650 -#> ds 4 m1 0 1.6 0.000e+00 1.600000 -2.429424 -#> ds 4 m1 1 0.9 6.826e-01 0.217363 -0.309476 -#> ds 4 m1 3 3.7 1.935e+00 1.765082 -2.255277 -#> ds 4 m1 3 2.0 1.935e+00 0.065082 -0.083157 -#> ds 4 m1 7 3.6 4.035e+00 -0.434805 0.474018 -#> ds 4 m1 7 3.8 4.035e+00 -0.234805 0.255981 -#> ds 4 m1 14 7.1 6.652e+00 0.448187 -0.413053 -#> ds 4 m1 14 6.6 6.652e+00 -0.051813 0.047751 -#> ds 4 m1 28 9.5 9.156e+00 0.343805 -0.276011 -#> ds 4 m1 28 9.3 9.156e+00 0.143805 -0.115448 -#> ds 4 m1 60 8.3 8.848e+00 -0.547762 0.446843 -#> ds 4 m1 60 9.0 8.848e+00 0.152238 -0.124190 -#> ds 4 m1 90 6.6 6.674e+00 -0.073979 0.068090 -#> ds 4 m1 90 7.7 6.674e+00 1.026021 -0.944353 -#> ds 4 m1 120 3.7 4.668e+00 -0.967537 1.010122 -#> ds 4 m1 120 3.5 4.668e+00 -1.167537 1.218925 -#> ds 5 parent 0 110.4 1.022e+02 8.170986 -1.132847 -#> ds 5 parent 0 112.1 1.022e+02 9.870986 -1.368539 -#> ds 5 parent 1 93.5 9.513e+01 -1.630764 0.241319 -#> ds 5 parent 1 91.0 9.513e+01 -4.130764 0.611268 -#> ds 5 parent 3 71.0 8.296e+01 -11.964279 2.001495 -#> ds 5 parent 3 89.7 8.296e+01 6.735721 -1.126813 -#> ds 5 parent 7 60.4 6.495e+01 -4.547441 0.942951 -#> ds 5 parent 7 59.1 6.495e+01 -5.847441 1.212518 -#> ds 5 parent 14 56.5 4.626e+01 10.241319 -2.825682 -#> ds 5 parent 14 47.0 4.626e+01 0.741319 -0.204537 -#> ds 5 parent 28 30.2 3.026e+01 -0.058478 0.022504 -#> ds 5 parent 28 23.9 3.026e+01 -6.358478 2.446932 -#> ds 5 parent 60 17.0 1.792e+01 -0.919046 0.508481 -#> ds 5 parent 60 18.7 1.792e+01 0.780954 -0.432079 -#> ds 5 parent 90 11.3 1.187e+01 -0.573917 0.404206 -#> ds 5 parent 90 11.9 1.187e+01 0.026083 -0.018370 -#> ds 5 parent 120 9.0 7.898e+00 1.102089 -0.946039 -#> ds 5 parent 120 8.1 7.898e+00 0.202089 -0.173474 -#> ds 5 m1 0 0.7 -1.421e-14 0.700000 -1.062873 -#> ds 5 m1 1 3.0 3.144e+00 -0.143526 0.166865 -#> ds 5 m1 1 2.6 3.144e+00 -0.543526 0.631910 -#> ds 5 m1 3 5.1 8.390e+00 -3.290265 2.749870 -#> ds 5 m1 3 7.5 8.390e+00 -0.890265 0.744048 -#> ds 5 m1 7 16.5 1.566e+01 0.841368 -0.506082 -#> ds 5 m1 7 19.0 1.566e+01 3.341368 -2.009830 -#> ds 5 m1 14 22.9 2.188e+01 1.017753 -0.493689 -#> ds 5 m1 14 23.2 2.188e+01 1.317753 -0.639212 -#> ds 5 m1 28 22.2 2.386e+01 -1.655914 0.756794 -#> ds 5 m1 28 24.4 2.386e+01 0.544086 -0.248661 -#> ds 5 m1 60 15.5 1.859e+01 -3.091124 1.670405 -#> ds 5 m1 60 19.8 1.859e+01 1.208876 -0.653262 -#> ds 5 m1 90 14.9 1.372e+01 1.176815 -0.764948 -#> ds 5 m1 90 14.2 1.372e+01 0.476815 -0.309937 -#> ds 5 m1 120 10.9 9.961e+00 0.938796 -0.723690 -#> ds 5 m1 120 10.4 9.961e+00 0.438796 -0.338255
    # } +#> ds name time observed predicted residual std standardized +#> ds 1 parent 0 89.8 9.869e+01 8.894553 6.3618 1.398124 +#> ds 1 parent 0 104.1 9.869e+01 -5.405447 6.3618 -0.849676 +#> ds 1 parent 1 88.7 9.413e+01 5.426448 6.0706 0.893897 +#> ds 1 parent 1 95.5 9.413e+01 -1.373552 6.0706 -0.226265 +#> ds 1 parent 3 81.8 8.576e+01 3.961821 5.5377 0.715422 +#> ds 1 parent 3 94.5 8.576e+01 -8.738179 5.5377 -1.577932 +#> ds 1 parent 7 71.5 7.168e+01 0.184828 4.6429 0.039809 +#> ds 1 parent 7 70.3 7.168e+01 1.384828 4.6429 0.298270 +#> ds 1 parent 14 54.2 5.351e+01 -0.688235 3.4934 -0.197008 +#> ds 1 parent 14 49.6 5.351e+01 3.911765 3.4934 1.119747 +#> ds 1 parent 28 31.5 3.209e+01 0.590445 2.1603 0.273322 +#> ds 1 parent 28 28.8 3.209e+01 3.290445 2.1603 1.523177 +#> ds 1 parent 60 12.1 1.272e+01 0.618158 1.0481 0.589761 +#> ds 1 parent 60 13.6 1.272e+01 -0.881842 1.0481 -0.841332 +#> ds 1 parent 90 6.2 6.085e+00 -0.115212 0.7655 -0.150512 +#> ds 1 parent 90 8.3 6.085e+00 -2.215212 0.7655 -2.893953 +#> ds 1 parent 120 2.2 3.009e+00 0.809439 0.6863 1.179470 +#> ds 1 parent 120 2.4 3.009e+00 0.609439 0.6863 0.888041 +#> ds 1 m1 1 0.3 1.129e+00 0.828817 0.6626 1.250938 +#> ds 1 m1 1 0.2 1.129e+00 0.928817 0.6626 1.401869 +#> ds 1 m1 3 2.2 3.141e+00 0.940880 0.6887 1.366187 +#> ds 1 m1 3 3.0 3.141e+00 0.140880 0.6887 0.204562 +#> ds 1 m1 7 6.5 6.326e+00 -0.174162 0.7735 -0.225175 +#> ds 1 m1 7 5.0 6.326e+00 1.325838 0.7735 1.714181 +#> ds 1 m1 14 10.2 9.883e+00 -0.317417 0.9139 -0.347326 +#> ds 1 m1 14 9.5 9.883e+00 0.382583 0.9139 0.418631 +#> ds 1 m1 28 12.2 1.251e+01 0.309856 1.0378 0.298572 +#> ds 1 m1 28 13.4 1.251e+01 -0.890144 1.0378 -0.857726 +#> ds 1 m1 60 11.8 1.086e+01 -0.940009 0.9584 -0.980812 +#> ds 1 m1 60 13.2 1.086e+01 -2.340009 0.9584 -2.441581 +#> ds 1 m1 90 6.6 7.823e+00 1.222977 0.8278 1.477332 +#> ds 1 m1 90 9.3 7.823e+00 -1.477023 0.8278 -1.784214 +#> ds 1 m1 120 3.5 5.315e+00 1.815201 0.7415 2.447906 +#> ds 1 m1 120 5.4 5.315e+00 -0.084799 0.7415 -0.114356 +#> ds 2 parent 0 118.0 1.031e+02 -14.876736 6.6443 -2.239038 +#> ds 2 parent 0 99.8 1.031e+02 3.323264 6.6443 0.500171 +#> ds 2 parent 1 90.2 9.757e+01 7.371379 6.2902 1.171891 +#> ds 2 parent 1 94.6 9.757e+01 2.971379 6.2902 0.472386 +#> ds 2 parent 3 96.1 8.788e+01 -8.222746 5.6724 -1.449599 +#> ds 2 parent 3 78.4 8.788e+01 9.477254 5.6724 1.670758 +#> ds 2 parent 7 77.9 7.293e+01 -4.972272 4.7218 -1.053054 +#> ds 2 parent 7 77.7 7.293e+01 -4.772272 4.7218 -1.010697 +#> ds 2 parent 14 56.0 5.602e+01 0.016773 3.6513 0.004594 +#> ds 2 parent 14 54.7 5.602e+01 1.316773 3.6513 0.360633 +#> ds 2 parent 28 36.6 3.855e+01 1.945779 2.5575 0.760803 +#> ds 2 parent 28 36.8 3.855e+01 1.745779 2.5575 0.682603 +#> ds 2 parent 60 22.1 2.101e+01 -1.086693 1.4996 -0.724663 +#> ds 2 parent 60 24.7 2.101e+01 -3.686693 1.4996 -2.458475 +#> ds 2 parent 90 12.4 1.246e+01 0.058759 1.0353 0.056757 +#> ds 2 parent 90 10.8 1.246e+01 1.658759 1.0353 1.602256 +#> ds 2 parent 120 6.8 7.406e+00 0.606226 0.8119 0.746659 +#> ds 2 parent 120 7.9 7.406e+00 -0.493774 0.8119 -0.608157 +#> ds 2 m1 1 1.3 1.438e+00 0.138236 0.6650 0.207869 +#> ds 2 m1 3 3.7 3.879e+00 0.178617 0.7040 0.253726 +#> ds 2 m1 3 4.7 3.879e+00 -0.821383 0.7040 -1.166780 +#> ds 2 m1 7 8.1 7.389e+00 -0.710951 0.8113 -0.876337 +#> ds 2 m1 7 7.9 7.389e+00 -0.510951 0.8113 -0.629812 +#> ds 2 m1 14 10.1 1.069e+01 0.593533 0.9507 0.624328 +#> ds 2 m1 14 10.3 1.069e+01 0.393533 0.9507 0.413951 +#> ds 2 m1 28 10.7 1.240e+01 1.703647 1.0325 1.649956 +#> ds 2 m1 28 12.2 1.240e+01 0.203647 1.0325 0.197229 +#> ds 2 m1 60 10.7 1.055e+01 -0.147672 0.9442 -0.156405 +#> ds 2 m1 60 12.5 1.055e+01 -1.947672 0.9442 -2.062848 +#> ds 2 m1 90 9.1 8.010e+00 -1.090041 0.8351 -1.305210 +#> ds 2 m1 90 7.4 8.010e+00 0.609959 0.8351 0.730362 +#> ds 2 m1 120 6.1 5.793e+00 -0.306797 0.7561 -0.405759 +#> ds 2 m1 120 4.5 5.793e+00 1.293203 0.7561 1.710347 +#> ds 3 parent 0 106.2 1.035e+02 -2.712344 6.6675 -0.406801 +#> ds 3 parent 0 106.9 1.035e+02 -3.412344 6.6675 -0.511788 +#> ds 3 parent 1 107.4 9.548e+01 -11.924044 6.1566 -1.936801 +#> ds 3 parent 1 96.1 9.548e+01 -0.624044 6.1566 -0.101362 +#> ds 3 parent 3 79.4 8.246e+01 3.056105 5.3274 0.573662 +#> ds 3 parent 3 82.6 8.246e+01 -0.143895 5.3274 -0.027010 +#> ds 3 parent 7 63.9 6.489e+01 0.991141 4.2122 0.235304 +#> ds 3 parent 7 62.4 6.489e+01 2.491141 4.2122 0.591416 +#> ds 3 parent 14 51.0 4.869e+01 -2.306824 3.1906 -0.723013 +#> ds 3 parent 14 47.1 4.869e+01 1.593176 3.1906 0.499338 +#> ds 3 parent 28 36.1 3.480e+01 -1.304261 2.3260 -0.560722 +#> ds 3 parent 28 36.6 3.480e+01 -1.804261 2.3260 -0.775679 +#> ds 3 parent 60 20.1 1.988e+01 -0.221952 1.4346 -0.154719 +#> ds 3 parent 60 19.8 1.988e+01 0.078048 1.4346 0.054406 +#> ds 3 parent 90 11.3 1.194e+01 0.642458 1.0099 0.636132 +#> ds 3 parent 90 10.7 1.194e+01 1.242458 1.0099 1.230224 +#> ds 3 parent 120 8.2 7.176e+00 -1.023847 0.8034 -1.274423 +#> ds 3 parent 120 7.3 7.176e+00 -0.123847 0.8034 -0.154158 +#> ds 3 m1 0 0.8 8.527e-13 -0.800000 0.6586 -1.214712 +#> ds 3 m1 1 1.8 1.856e+00 0.055925 0.6693 0.083562 +#> ds 3 m1 1 2.3 1.856e+00 -0.444075 0.6693 -0.663537 +#> ds 3 m1 3 4.2 4.780e+00 0.580164 0.7264 0.798676 +#> ds 3 m1 3 4.1 4.780e+00 0.680164 0.7264 0.936340 +#> ds 3 m1 7 6.8 8.410e+00 1.609920 0.8512 1.891455 +#> ds 3 m1 7 10.1 8.410e+00 -1.690080 0.8512 -1.985633 +#> ds 3 m1 14 11.4 1.098e+01 -0.424444 0.9638 -0.440389 +#> ds 3 m1 14 12.8 1.098e+01 -1.824444 0.9638 -1.892979 +#> ds 3 m1 28 11.5 1.142e+01 -0.079336 0.9848 -0.080558 +#> ds 3 m1 28 10.6 1.142e+01 0.820664 0.9848 0.833311 +#> ds 3 m1 60 7.5 9.110e+00 1.610231 0.8803 1.829222 +#> ds 3 m1 60 8.6 9.110e+00 0.510231 0.8803 0.579622 +#> ds 3 m1 90 7.3 6.799e+00 -0.501085 0.7898 -0.634463 +#> ds 3 m1 90 8.1 6.799e+00 -1.301085 0.7898 -1.647404 +#> ds 3 m1 120 5.3 4.868e+00 -0.431505 0.7288 -0.592064 +#> ds 3 m1 120 3.8 4.868e+00 1.068495 0.7288 1.466073 +#> ds 4 parent 0 104.7 9.926e+01 -5.444622 6.3975 -0.851049 +#> ds 4 parent 0 88.3 9.926e+01 10.955378 6.3975 1.712436 +#> ds 4 parent 1 94.2 9.618e+01 1.978413 6.2013 0.319030 +#> ds 4 parent 1 94.6 9.618e+01 1.578413 6.2013 0.254527 +#> ds 4 parent 3 78.1 9.037e+01 12.268550 5.8311 2.103985 +#> ds 4 parent 3 96.5 9.037e+01 -6.131450 5.8311 -1.051508 +#> ds 4 parent 7 76.2 7.999e+01 3.794958 5.1708 0.733918 +#> ds 4 parent 7 77.8 7.999e+01 2.194958 5.1708 0.424489 +#> ds 4 parent 14 70.8 6.518e+01 -5.624996 4.2301 -1.329742 +#> ds 4 parent 14 67.3 6.518e+01 -2.124996 4.2301 -0.502346 +#> ds 4 parent 28 43.1 4.462e+01 1.517860 2.9354 0.517085 +#> ds 4 parent 28 45.1 4.462e+01 -0.482140 2.9354 -0.164249 +#> ds 4 parent 60 21.3 2.130e+01 -0.003305 1.5159 -0.002180 +#> ds 4 parent 60 23.5 2.130e+01 -2.203305 1.5159 -1.453435 +#> ds 4 parent 90 11.8 1.180e+01 0.002834 1.0032 0.002825 +#> ds 4 parent 90 12.1 1.180e+01 -0.297166 1.0032 -0.296226 +#> ds 4 parent 120 7.0 6.868e+00 -0.132251 0.7922 -0.166937 +#> ds 4 parent 120 6.2 6.868e+00 0.667749 0.7922 0.842879 +#> ds 4 m1 0 1.6 0.000e+00 -1.600000 0.6586 -2.429424 +#> ds 4 m1 1 0.9 6.826e-01 -0.217363 0.6600 -0.329315 +#> ds 4 m1 3 3.7 1.935e+00 -1.765082 0.6702 -2.633768 +#> ds 4 m1 3 2.0 1.935e+00 -0.065082 0.6702 -0.097112 +#> ds 4 m1 7 3.6 4.035e+00 0.434805 0.7076 0.614501 +#> ds 4 m1 7 3.8 4.035e+00 0.234805 0.7076 0.331845 +#> ds 4 m1 14 7.1 6.652e+00 -0.448187 0.7846 -0.571220 +#> ds 4 m1 14 6.6 6.652e+00 0.051813 0.7846 0.066036 +#> ds 4 m1 28 9.5 9.156e+00 -0.343805 0.8822 -0.389696 +#> ds 4 m1 28 9.3 9.156e+00 -0.143805 0.8822 -0.163000 +#> ds 4 m1 60 8.3 8.848e+00 0.547762 0.8692 0.630185 +#> ds 4 m1 60 9.0 8.848e+00 -0.152238 0.8692 -0.175146 +#> ds 4 m1 90 6.6 6.674e+00 0.073979 0.7854 0.094194 +#> ds 4 m1 90 7.7 6.674e+00 -1.026021 0.7854 -1.306390 +#> ds 4 m1 120 3.7 4.668e+00 0.967537 0.7234 1.337503 +#> ds 4 m1 120 3.5 4.668e+00 1.167537 0.7234 1.613979 +#> ds 5 parent 0 110.4 1.022e+02 -8.170986 6.5872 -1.240433 +#> ds 5 parent 0 112.1 1.022e+02 -9.870986 6.5872 -1.498509 +#> ds 5 parent 1 93.5 9.513e+01 1.630764 6.1346 0.265832 +#> ds 5 parent 1 91.0 9.513e+01 4.130764 6.1346 0.673359 +#> ds 5 parent 3 71.0 8.296e+01 11.964279 5.3597 2.232268 +#> ds 5 parent 3 89.7 8.296e+01 -6.735721 5.3597 -1.256735 +#> ds 5 parent 7 60.4 6.495e+01 4.547441 4.2157 1.078684 +#> ds 5 parent 7 59.1 6.495e+01 5.847441 4.2157 1.387053 +#> ds 5 parent 14 56.5 4.626e+01 -10.241319 3.0380 -3.371047 +#> ds 5 parent 14 47.0 4.626e+01 -0.741319 3.0380 -0.244014 +#> ds 5 parent 28 30.2 3.026e+01 0.058478 2.0487 0.028544 +#> ds 5 parent 28 23.9 3.026e+01 6.358478 2.0487 3.103661 +#> ds 5 parent 60 17.0 1.792e+01 0.919046 1.3242 0.694024 +#> ds 5 parent 60 18.7 1.792e+01 -0.780954 1.3242 -0.589742 +#> ds 5 parent 90 11.3 1.187e+01 0.573917 1.0066 0.570144 +#> ds 5 parent 90 11.9 1.187e+01 -0.026083 1.0066 -0.025912 +#> ds 5 parent 120 9.0 7.898e+00 -1.102089 0.8307 -1.326622 +#> ds 5 parent 120 8.1 7.898e+00 -0.202089 0.8307 -0.243261 +#> ds 5 m1 0 0.7 -1.421e-14 -0.700000 0.6586 -1.062873 +#> ds 5 m1 1 3.0 3.144e+00 0.143526 0.6887 0.208390 +#> ds 5 m1 1 2.6 3.144e+00 0.543526 0.6887 0.789161 +#> ds 5 m1 3 5.1 8.390e+00 3.290265 0.8504 3.869277 +#> ds 5 m1 3 7.5 8.390e+00 0.890265 0.8504 1.046932 +#> ds 5 m1 7 16.5 1.566e+01 -0.841368 1.2007 -0.700751 +#> ds 5 m1 7 19.0 1.566e+01 -3.341368 1.2007 -2.782928 +#> ds 5 m1 14 22.9 2.188e+01 -1.017753 1.5498 -0.656687 +#> ds 5 m1 14 23.2 2.188e+01 -1.317753 1.5498 -0.850257 +#> ds 5 m1 28 22.2 2.386e+01 1.655914 1.6652 0.994399 +#> ds 5 m1 28 24.4 2.386e+01 -0.544086 1.6652 -0.326731 +#> ds 5 m1 60 15.5 1.859e+01 3.091124 1.3618 2.269915 +#> ds 5 m1 60 19.8 1.859e+01 -1.208876 1.3618 -0.887718 +#> ds 5 m1 90 14.9 1.372e+01 -1.176815 1.0990 -1.070784 +#> ds 5 m1 90 14.2 1.372e+01 -0.476815 1.0990 -0.433854 +#> ds 5 m1 120 10.9 9.961e+00 -0.938796 0.9174 -1.023332 +#> ds 5 m1 120 10.4 9.961e+00 -0.438796 0.9174 -0.478308
    # }
    diff --git a/docs/dev/reference/transform_odeparms.html b/docs/dev/reference/transform_odeparms.html index 6b849d3f..0845d478 100644 --- a/docs/dev/reference/transform_odeparms.html +++ b/docs/dev/reference/transform_odeparms.html @@ -252,7 +252,7 @@ This is no problem for the internal use in mkinfit.# \dontrun{# Compare to the version without transforming rate parametersfit.2<-mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates =FALSE, quiet =TRUE) -
    #> Warning: Observations with value of zero were removed from the data
    #> Error in if (cost < cost.current) { assign("cost.current", cost, inherits = TRUE) if (!quiet) cat(ifelse(OLS, "Sum of squared residuals", "Negative log-likelihood"), " at call ", calls, ": ", signif(cost.current, 6), "\n", sep = "")}: missing value where TRUE/FALSE needed
    #> Timing stopped at: 0.003 0 0.002
    fit.2.s <- summary(fit.2) +
    #> Warning: Observations with value of zero were removed from the data
    #> Error in if (cost < cost.current) { assign("cost.current", cost, inherits = TRUE) if (!quiet) cat(ifelse(OLS, "Sum of squared residuals", "Negative log-likelihood"), " at call ", calls, ": ", signif(cost.current, 6), "\n", sep = "")}: missing value where TRUE/FALSE needed
    #> Timing stopped at: 0.002 0 0.003
    fit.2.s <- summary(fit.2)
    #> Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'fit.2' not found
    print(fit.2.s$par, 3)
    #> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found
    print(fit.2.s$bpar, 3)
    #> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'print': object 'fit.2.s' not found
    # } diff --git a/docs/dev/sitemap.xml b/docs/dev/sitemap.xml index 02fca7f9..31b0abb1 100644 --- a/docs/dev/sitemap.xml +++ b/docs/dev/sitemap.xml @@ -9,6 +9,9 @@ https://pkgdown.jrwb.de/mkin/reference/CAKE_export.html + + https://pkgdown.jrwb.de/mkin/reference/D24_2014.html + https://pkgdown.jrwb.de/mkin/reference/DFOP.solution.html @@ -69,6 +72,12 @@ https://pkgdown.jrwb.de/mkin/reference/experimental_data_for_UBA.html + + https://pkgdown.jrwb.de/mkin/reference/f_time_norm_focus.html + + + https://pkgdown.jrwb.de/mkin/reference/focus_soil_moisture.html + https://pkgdown.jrwb.de/mkin/reference/get_deg_func.html @@ -102,6 +111,9 @@ https://pkgdown.jrwb.de/mkin/reference/mkinds.html + + https://pkgdown.jrwb.de/mkin/reference/mkindsg.html + https://pkgdown.jrwb.de/mkin/reference/mkinerrmin.html @@ -126,9 +138,6 @@ https://pkgdown.jrwb.de/mkin/reference/mkinresplot.html - - https://pkgdown.jrwb.de/mkin/reference/mkinsub.html - https://pkgdown.jrwb.de/mkin/reference/mmkin.html @@ -159,12 +168,6 @@ https://pkgdown.jrwb.de/mkin/reference/plot.nafta.html - - https://pkgdown.jrwb.de/mkin/reference/print.mkinds.html - - - https://pkgdown.jrwb.de/mkin/reference/print.mkinmod.html - https://pkgdown.jrwb.de/mkin/reference/print.mmkin.html -- cgit v1.2.1