diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2021-02-04 11:24:22 +0100 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2021-02-04 11:41:06 +0100 |
| commit | ac183c732317cf6ede26a2ee127604a407f0a6b3 (patch) | |
| tree | 2283709a2e01206af576a9cf324f54fbfab972d0 | |
| parent | 83798cce97e73ec3bfd11b8cb4e2929e5089aaeb (diff) | |
Documentation improvements, mainly fixing example code
The errors in the example code were in the \dontrun sections, so they
were not caught by CRAN checks. In addition, the static help files
generated with pkgdown were cached, so I noticed the errors only
after completely regenerating the documentation for version 1.0.0.
42 files changed, 266 insertions, 217 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index 8bef6055..70872c1d 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,8 +1,8 @@ Package: mkin Type: Package Title: Kinetic Evaluation of Chemical Degradation Data -Version: 1.0.0 -Date: 2021-02-03 +Version: 1.0.1 +Date: 2021-02-04 Authors@R: c( person("Johannes", "Ranke", role = c("aut", "cre", "cph"), email = "jranke@uni-bremen.de", @@ -1,3 +1,11 @@ +# mkin 1.0.1 + +- 'confint.mmkin', 'nlme.mmkin', 'transform_odeparms': Fix example code in dontrun sections that failed with current defaults + +- 'logLik.mkinfit': Improve example code to avoid warnings and show convenient syntax + +- 'mkinresplot': Re-add Katrin Lindenberger as coauthor who was accidentally removed long ago + # mkin 1.0.0 ## General diff --git a/R/confint.mkinfit.R b/R/confint.mkinfit.R index 53eb45ee..6403c349 100644 --- a/R/confint.mkinfit.R +++ b/R/confint.mkinfit.R @@ -57,20 +57,20 @@ #' if (identical(Sys.getenv("NOT_CRAN"), "true")) { #' n_cores <- parallel::detectCores() - 1 #' } else { -#' n_cores <- 1 +#' 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 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), +#' use_of_ff = "min", 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)) #' # 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 +#' # minor interest), we get a nice performance improvement if we use at least 4 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)) #' ci_profile diff --git a/R/logLik.mkinfit.R b/R/logLik.mkinfit.R index 1c025893..7cc10234 100644 --- a/R/logLik.mkinfit.R +++ b/R/logLik.mkinfit.R @@ -25,10 +25,10 @@ #' parent = mkinsub("SFO", to = "m1"), #' m1 = mkinsub("SFO") #' ) -#' d_t <- FOCUS_2006_D +#' d_t <- subset(FOCUS_2006_D, value != 0) #' f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity) -#' f_obs <- mkinfit(sfo_sfo, d_t, error_model = "obs", quiet = TRUE) -#' f_tc <- mkinfit(sfo_sfo, d_t, error_model = "tc", quiet = TRUE) +#' f_obs <- update(f_nw, error_model = "obs") +#' f_tc <- update(f_nw, error_model = "tc") #' AIC(f_nw, f_obs, f_tc) #' } #' diff --git a/R/mkinfit.R b/R/mkinfit.R index d7de718b..704e70a9 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -542,6 +542,8 @@ mkinfit <- function(mkinmod, observed, { assign("calls", calls + 1, inherits = TRUE) # Increase the model solution counter + #browser() + # Trace parameter values if requested and if we are actually optimising if(trace_parms & update_data) cat(format(P, width = 10, digits = 6), "\n") diff --git a/R/mkinresplot.R b/R/mkinresplot.R index bad28ae8..be361690 100644 --- a/R/mkinresplot.R +++ b/R/mkinresplot.R @@ -28,7 +28,7 @@ utils::globalVariables(c("variable", "residual")) #' @param \dots further arguments passed to \code{\link{plot}}. #' @return Nothing is returned by this function, as it is called for its side #' effect, namely to produce a plot. -#' @author Johannes Ranke +#' @author Johannes Ranke and Katrin Lindenberger #' @seealso \code{\link{mkinplot}}, for a way to plot the data and the fitted #' lines of the mkinfit object, and \code{\link{plot_res}} for a function #' combining the plot of the fit and the residual plot. @@ -162,6 +162,7 @@ mmkin <- function(models = c("SFO", "FOMC", "DFOP"), datasets, #' #' @param x An [mmkin] object. #' @param \dots Not used. +#' @rdname mmkin #' @export print.mmkin <- function(x, ...) { cat("<mmkin> object\n") diff --git a/R/nlme.mmkin.R b/R/nlme.mmkin.R index 82d5f6de..ff1f2fff 100644 --- a/R/nlme.mmkin.R +++ b/R/nlme.mmkin.R @@ -24,6 +24,11 @@ get_deg_func <- function() { #' This functions sets up a nonlinear mixed effects model for an mmkin row #' object. An mmkin row object is essentially a list of mkinfit objects that #' have been obtained by fitting the same model to a list of datasets. +#' +#' Note that the convergence of the nlme algorithms depends on the quality +#' of the data. In degradation kinetics, we often only have few datasets +#' (e.g. data for few soils) and complicated degradation models, which may +#' make it impossible to obtain convergence with nlme. #' #' @param model An [mmkin] row object. #' @param data Ignored, data are taken from the mmkin model @@ -88,11 +93,10 @@ get_deg_func <- function() { #' # f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ]) #' #plot(f_nlme_sfo_sfo_ff) #' -#' # With the log-Cholesky parameterization, this converges in 11 -#' # iterations and around 100 seconds, but without tweaking control -#' # parameters (with pdDiag, increasing the tolerance and pnlsMaxIter was -#' # necessary) -#' f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ]) +#' # For the following, we need to increase pnlsMaxIter and the tolerance +#' # to get convergence +#' f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ], +#' control = list(pnlsMaxIter = 120, tolerance = 5e-4)) #' #' plot(f_nlme_dfop_sfo) #' @@ -112,22 +116,18 @@ get_deg_func <- function() { #' print(f_nlme_dfop_tc) #' } #' -#' f_2_obs <- mmkin(list("SFO-SFO" = m_sfo_sfo, -#' "DFOP-SFO" = m_dfop_sfo), -#' ds_2, quiet = TRUE, error_model = "obs") +#' f_2_obs <- update(f_2, error_model = "obs") #' f_nlme_sfo_sfo_obs <- nlme(f_2_obs["SFO-SFO", ]) #' print(f_nlme_sfo_sfo_obs) -#' f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ]) +#' f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ], +#' control = list(pnlsMaxIter = 120, tolerance = 5e-4)) #' -#' f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo, -#' "DFOP-SFO" = m_dfop_sfo), -#' ds_2, quiet = TRUE, error_model = "tc") -#' # f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # stops with error message -#' f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ]) -#' # We get warnings about false convergence in the LME step in several iterations -#' # but as the last such warning occurs in iteration 25 and we have 28 iterations -#' # we can ignore these -#' anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs, f_nlme_dfop_sfo_tc) +#' f_2_tc <- update(f_2, error_model = "tc") +#' # f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations +#' # f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ], +#' # control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm +#' +#' anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs) #' #' } nlme.mmkin <- function(model, data = "auto", diff --git a/R/transform_odeparms.R b/R/transform_odeparms.R index f21d31fc..4fe4e5c2 100644 --- a/R/transform_odeparms.R +++ b/R/transform_odeparms.R @@ -42,17 +42,21 @@ #' #' SFO_SFO <- mkinmod( #' parent = list(type = "SFO", to = "m1", sink = TRUE), -#' m1 = list(type = "SFO")) +#' m1 = list(type = "SFO"), use_of_ff = "min") +#' #' # Fit the model to the FOCUS example dataset D using defaults -#' fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE) +#' FOCUS_D <- subset(FOCUS_2006_D, value != 0) # remove zero values to avoid warning +#' fit <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE) #' fit.s <- summary(fit) #' # Transformed and backtransformed parameters #' print(fit.s$par, 3) #' print(fit.s$bpar, 3) #' #' \dontrun{ -#' # Compare to the version without transforming rate parameters -#' fit.2 <- mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates = FALSE, quiet = TRUE) +#' # Compare to the version without transforming rate parameters (does not work +#' # with analytical solution, we get NA values for m1 in predictions) +#' fit.2 <- mkinfit(SFO_SFO, FOCUS_D, transform_rates = FALSE, +#' solution_type = "deSolve", quiet = TRUE) #' fit.2.s <- summary(fit.2) #' print(fit.2.s$par, 3) #' print(fit.2.s$bpar, 3) @@ -66,13 +70,13 @@ #' backtransform_odeparms(transformed, SFO_SFO) #' #' \dontrun{ -#' # The case of formation fractions +#' # The case of formation fractions (this is now the default) #' SFO_SFO.ff <- mkinmod( #' parent = list(type = "SFO", to = "m1", sink = TRUE), #' m1 = list(type = "SFO"), #' use_of_ff = "max") #' -#' fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE) +#' fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_D, quiet = TRUE) #' fit.ff.s <- summary(fit.ff) #' print(fit.ff.s$par, 3) #' print(fit.ff.s$bpar, 3) @@ -87,7 +91,7 @@ #' use_of_ff = "max") #' #' -#' fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D, quiet = TRUE) +#' fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_D, quiet = TRUE) #' fit.ff.2.s <- summary(fit.ff.2) #' print(fit.ff.2.s$par, 3) #' print(fit.ff.2.s$bpar, 3) @@ -100,6 +100,8 @@ version is found in the ['dev' subdirectory](https://pkgdown.jrwb.de/mkin/dev/). * Nonlinear mixed-effects models can be created from fits of the same degradation model to different datasets for the same compound by using the [nlme.mmkin](https://pkgdown.jrwb.de/mkin/reference/nlme.mmkin.html) method. + Note that the convergence of the nlme fits depends on the quality of the data. + Convergence is better for simple models and data for many groups (e.g. soils). ## GUI diff --git a/_pkgdown.yml b/_pkgdown.yml index 7d66f5b0..f632ddb0 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -35,7 +35,6 @@ reference: - "`[.mmkin`" - plot.mmkin - AIC.mmkin - - print.mmkin - title: Mixed models desc: Create and work with nonlinear mixed effects models contents: @@ -6,5 +6,5 @@ * creating vignettes ... OK * checking for LF line-endings in source and make files and shell scripts * checking for empty or unneeded directories -* building ‘mkin_1.0.0.tar.gz’ +* building ‘mkin_1.0.1.tar.gz’ @@ -5,7 +5,7 @@ * using options ‘--no-tests --as-cran’ * checking for file ‘mkin/DESCRIPTION’ ... OK * checking extension type ... Package -* this is package ‘mkin’ version ‘1.0.0’ +* this is package ‘mkin’ version ‘1.0.1’ * package encoding: UTF-8 * checking CRAN incoming feasibility ... Note_to_CRAN_maintainers Maintainer: ‘Johannes Ranke <jranke@uni-bremen.de>’ diff --git a/docs/404.html b/docs/404.html index 42423c5d..45a45f3e 100644 --- a/docs/404.html +++ b/docs/404.html @@ -71,7 +71,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="https://pkgdown.jrwb.de/mkin/index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> diff --git a/docs/articles/index.html b/docs/articles/index.html index 369b506c..66393487 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -71,7 +71,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> diff --git a/docs/authors.html b/docs/authors.html index f5c6160c..0f68e2ce 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -71,7 +71,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> diff --git a/docs/index.html b/docs/index.html index c7b2e277..bcdaa7e4 100644 --- a/docs/index.html +++ b/docs/index.html @@ -37,7 +37,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> @@ -146,7 +146,7 @@ <li>Three different error models can be selected using the argument <code>error_model</code> to the <a href="https://pkgdown.jrwb.de/mkin/reference/mkinfit.html"><code>mkinfit</code></a> function.</li> <li>The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) should now be specified as <code>error_model = "obs"</code>.</li> <li>A two-component error model similar to the one proposed by <a href="https://pkgdown.jrwb.de/mkin/reference/sigma_twocomp.html">Rocke and Lorenzato</a> can be selected using the argument <code>error_model = "tc"</code>.</li> -<li>Nonlinear mixed-effects models can be created from fits of the same degradation model to different datasets for the same compound by using the <a href="https://pkgdown.jrwb.de/mkin/reference/nlme.mmkin.html">nlme.mmkin</a> method.</li> +<li>Nonlinear mixed-effects models can be created from fits of the same degradation model to different datasets for the same compound by using the <a href="https://pkgdown.jrwb.de/mkin/reference/nlme.mmkin.html">nlme.mmkin</a> method. Note that the convergence of the nlme fits depends on the quality of the data. Convergence is better for simple models and data for many groups (e.g. soils).</li> </ul> </div> <div id="gui" class="section level2"> diff --git a/docs/news/index.html b/docs/news/index.html index 88c7c49c..7a307709 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -71,7 +71,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> @@ -141,9 +141,19 @@ <small>Source: <a href='https://github.com/jranke/mkin/blob/master/NEWS.md'><code>NEWS.md</code></a></small> </div> + <div id="mkin-1-0-1" class="section level1"> +<h1 class="page-header" data-toc-text="1.0.1"> +<a href="#mkin-1-0-1" class="anchor"></a>mkin 1.0.1<small> Unreleased </small> +</h1> +<ul> +<li><p>‘confint.mmkin’, ‘nlme.mmkin’, ‘transform_odeparms’: Fix example code in dontrun sections that failed with current defaults</p></li> +<li><p>‘logLik.mkinfit’: Improve example code to avoid warnings and show convenient syntax</p></li> +<li><p>‘mkinresplot’: Re-add Katrin Lindenberger as coauthor who was accidentally removed long ago</p></li> +</ul> +</div> <div id="mkin-1-0-0" class="section level1"> <h1 class="page-header" data-toc-text="1.0.0"> -<a href="#mkin-1-0-0" class="anchor"></a>mkin 1.0.0<small> Unreleased </small> +<a href="#mkin-1-0-0" class="anchor"></a>mkin 1.0.0<small> 2021-02-03 </small> </h1> <div id="general" class="section level2"> <h2 class="hasAnchor"> diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index 6c5f8bc3..d05f3168 100644 --- a/docs/pkgdown.yml +++ b/docs/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: 2021-02-03T16:42Z +last_built: 2021-02-04T10:34Z urls: reference: https://pkgdown.jrwb.de/mkin/reference article: https://pkgdown.jrwb.de/mkin/articles diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png Binary files differindex 7f498242..17a35806 100644 --- a/docs/reference/Rplot001.png +++ b/docs/reference/Rplot001.png diff --git a/docs/reference/Rplot002.png b/docs/reference/Rplot002.png Binary files differindex 54c31a3f..bb624e64 100644 --- a/docs/reference/Rplot002.png +++ b/docs/reference/Rplot002.png diff --git a/docs/reference/Rplot003.png b/docs/reference/Rplot003.png Binary files differindex 19198739..e96adeb3 100644 --- a/docs/reference/Rplot003.png +++ b/docs/reference/Rplot003.png diff --git a/docs/reference/Rplot004.png b/docs/reference/Rplot004.png Binary files differindex ead98fba..91058d4b 100644 --- a/docs/reference/Rplot004.png +++ b/docs/reference/Rplot004.png diff --git a/docs/reference/Rplot005.png b/docs/reference/Rplot005.png Binary files differindex 949a9283..91058d4b 100644 --- a/docs/reference/Rplot005.png +++ b/docs/reference/Rplot005.png diff --git a/docs/reference/Rplot006.png b/docs/reference/Rplot006.png Binary files differindex da52f580..74f43dfa 100644 --- a/docs/reference/Rplot006.png +++ b/docs/reference/Rplot006.png diff --git a/docs/reference/confint.mkinfit.html b/docs/reference/confint.mkinfit.html index 4f7e8872..b71e039a 100644 --- a/docs/reference/confint.mkinfit.html +++ b/docs/reference/confint.mkinfit.html @@ -273,68 +273,69 @@ Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/identical.html'>identical</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.getenv.html'>Sys.getenv</a></span><span class='op'>(</span><span class='st'>"NOT_CRAN"</span><span class='op'>)</span>, <span class='st'>"true"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>{</span> <span class='va'>n_cores</span> <span class='op'><-</span> <span class='fu'>parallel</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span><span class='op'>(</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>1</span> <span class='op'>}</span> <span class='kw'>else</span> <span class='op'>{</span> - <span class='va'>n_cores</span> <span class='op'><-</span> <span class='fl'>1</span> + <span class='va'>n_cores</span> <span class='op'><-</span> <span class='fl'>1</span> <span class='op'>}</span> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.getenv.html'>Sys.getenv</a></span><span class='op'>(</span><span class='st'>"TRAVIS"</span><span class='op'>)</span> <span class='op'>!=</span> <span class='st'>""</span><span class='op'>)</span> <span class='va'>n_cores</span> <span class='op'>=</span> <span class='fl'>1</span> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>[</span><span class='st'>"sysname"</span><span class='op'>]</span> <span class='op'>==</span> <span class='st'>"Windows"</span><span class='op'>)</span> <span class='va'>n_cores</span> <span class='op'>=</span> <span class='fl'>1</span> -<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, + use_of_ff <span class='op'>=</span> <span class='st'>"min"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='va'>SFO_SFO.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='va'>f_d_1</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span><span class='va'>ci_profile</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"profile"</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span><span class='op'>)</span> </div><div class='output co'>#> user system elapsed -#> 3.796 1.056 3.506 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span> +#> 4.324 0.980 3.960 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span> <span class='co'># If we additionally exclude parent_0 (the confidence of which is often of</span> -<span class='co'># minor interest), we get a nice performance improvement from about 50</span> -<span class='co'># seconds to about 12 seconds if we use at least four cores</span> +<span class='co'># minor interest), we get a nice performance improvement if we use at least 4 cores</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span><span class='op'>(</span><span class='va'>ci_profile_no_parent_0</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"profile"</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"k_parent_sink"</span>, <span class='st'>"k_parent_m1"</span>, <span class='st'>"k_m1_sink"</span>, <span class='st'>"sigma"</span><span class='op'>)</span>, cores <span class='op'>=</span> <span class='va'>n_cores</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='output co'>#> <span class='warning'>Warning: scheduled cores 2, 1, 3 encountered errors in user code, all values of the jobs will be affected</span></div><div class='output co'>#> <span class='error'>Error in dimnames(x) <- dn: length of 'dimnames' [2] not equal to array extent</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0 0.043 0.246</span></div><div class='input'><span class='va'>ci_profile</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 96.456003640 1.027703e+02 -#> k_parent 0.090911032 1.071578e-01 -#> k_m1 0.003892606 6.702775e-03 -#> f_parent_to_m1 0.471328495 5.611550e-01 -#> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='va'>ci_quadratic_transformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='output co'>#> user system elapsed +#> 1.480 0.109 0.905 </div><div class='input'><span class='va'>ci_profile</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.456003640 1.027703e+02 +#> k_parent_sink 0.040762501 5.549764e-02 +#> k_parent_m1 0.046786482 5.500879e-02 +#> k_m1_sink 0.003892605 6.702778e-03 +#> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='va'>ci_quadratic_transformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span><span class='op'>)</span> <span class='va'>ci_quadratic_transformed</span> -</div><div class='output co'>#> 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</div><div class='input'><span class='va'>ci_quadratic_untransformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403841640 1.027931e+02 +#> k_parent_sink 0.041033378 5.596269e-02 +#> k_parent_m1 0.046777902 5.511931e-02 +#> k_m1_sink 0.004012217 6.897547e-03 +#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='va'>ci_quadratic_untransformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span><span class='op'>(</span><span class='va'>f_d_1</span>, method <span class='op'>=</span> <span class='st'>"quadratic"</span>, transformed <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span> <span class='va'>ci_quadratic_untransformed</span> -</div><div class='output co'>#> 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</div><div class='input'><span class='co'># Against the expectation based on Bates and Watts (1988), the confidence</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403841645 102.79312449 +#> k_parent_sink 0.040485331 0.05535491 +#> k_parent_m1 0.046611582 0.05494364 +#> k_m1_sink 0.003835483 0.00668582 +#> sigma 2.396089689 3.85491806</div><div class='input'><span class='co'># Against the expectation based on Bates and Watts (1988), the confidence</span> <span class='co'># intervals based on the internal parameter transformation are less</span> <span class='co'># congruent with the likelihood based intervals. Note the superiority of the</span> <span class='co'># interval based on the untransformed fit for k_m1_sink</span> <span class='va'>rel_diffs_transformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span><span class='op'>(</span><span class='op'>(</span><span class='va'>ci_quadratic_transformed</span> <span class='op'>-</span> <span class='va'>ci_profile</span><span class='op'>)</span><span class='op'>/</span><span class='va'>ci_profile</span><span class='op'>)</span> <span class='va'>rel_diffs_untransformed</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span><span class='op'>(</span><span class='op'>(</span><span class='va'>ci_quadratic_untransformed</span> <span class='op'>-</span> <span class='va'>ci_profile</span><span class='op'>)</span><span class='op'>/</span><span class='va'>ci_profile</span><span class='op'>)</span> <span class='va'>rel_diffs_transformed</span> <span class='op'><</span> <span class='va'>rel_diffs_untransformed</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 FALSE FALSE -#> k_parent TRUE TRUE -#> k_m1 FALSE FALSE -#> f_parent_to_m1 TRUE FALSE -#> sigma TRUE FALSE</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_transformed</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> 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</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_untransformed</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> 2.5% 97.5% -#> parent_0 0.000541 0.000222 -#> k_parent 0.004610 0.002370 -#> k_m1 0.014700 0.002530 -#> f_parent_to_m1 0.004700 0.002350 -#> sigma 0.055000 0.032700</div><div class='input'> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 FALSE FALSE +#> k_parent_sink TRUE FALSE +#> k_parent_m1 TRUE FALSE +#> k_m1_sink FALSE FALSE +#> sigma FALSE FALSE</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_transformed</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.000541 0.000222 +#> k_parent_sink 0.006650 0.008380 +#> k_parent_m1 0.000183 0.002010 +#> k_m1_sink 0.030700 0.029100 +#> sigma 0.055000 0.032700</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span><span class='op'>(</span><span class='va'>rel_diffs_untransformed</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.000541 0.000222 +#> k_parent_sink 0.006800 0.002570 +#> k_parent_m1 0.003740 0.001180 +#> k_m1_sink 0.014700 0.002530 +#> sigma 0.055000 0.032700</div><div class='input'> <span class='co'># Investigate a case with formation fractions</span> <span class='va'>f_d_2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> diff --git a/docs/reference/index.html b/docs/reference/index.html index c9f66992..0859a152 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -71,7 +71,7 @@ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> @@ -175,7 +175,7 @@ </tr><tr> <td> - <p><code><a href="mmkin.html">mmkin()</a></code> </p> + <p><code><a href="mmkin.html">mmkin()</a></code> <code><a href="mmkin.html">print(<i><mmkin></i>)</a></code> </p> </td> <td><p>Fit one or more kinetic models with one or more state variables to one or more datasets</p></td> @@ -297,12 +297,6 @@ of an mmkin object</p></td> <p><code><a href="AIC.mmkin.html">AIC(<i><mmkin></i>)</a></code> <code><a href="AIC.mmkin.html">BIC(<i><mmkin></i>)</a></code> </p> </td> <td><p>Calculate the AIC for a column of an mmkin object</p></td> - </tr><tr> - - <td> - <p><code><a href="print.mmkin.html">print(<i><mmkin></i>)</a></code> </p> - </td> - <td><p>Print method for mmkin objects</p></td> </tr> </tbody><tbody> <tr> diff --git a/docs/reference/logLik.mkinfit.html b/docs/reference/logLik.mkinfit.html index ac3f570c..8d984e55 100644 --- a/docs/reference/logLik.mkinfit.html +++ b/docs/reference/logLik.mkinfit.html @@ -196,11 +196,11 @@ and the fitted error model parameters.</p> parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span> <span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> <span class='va'>d_t</span> <span class='op'><-</span> <span class='va'>FOCUS_2006_D</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> <span class='va'>d_t</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='va'>f_nw</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> <span class='co'># no weighting (weights are unity)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='va'>f_obs</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='va'>f_tc</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>sfo_sfo</span>, <span class='va'>d_t</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f_nw</span>, <span class='va'>f_obs</span>, <span class='va'>f_tc</span><span class='op'>)</span> + <span class='va'>f_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_nw</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> + <span class='va'>f_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_nw</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> + <span class='fu'><a href='https://rdrr.io/r/stats/AIC.html'>AIC</a></span><span class='op'>(</span><span class='va'>f_nw</span>, <span class='va'>f_obs</span>, <span class='va'>f_tc</span><span class='op'>)</span> </div><div class='output co'>#> df AIC #> f_nw 5 204.4486 #> f_obs 6 205.8727 diff --git a/docs/reference/mkinresplot.html b/docs/reference/mkinresplot.html index a9638c93..69517f36 100644 --- a/docs/reference/mkinresplot.html +++ b/docs/reference/mkinresplot.html @@ -242,7 +242,7 @@ lines of the mkinfit object, and <code><a href='plot.mkinfit.html'>plot_res</a>< combining the plot of the fit and the residual plot.</p></div> <h2 class="hasAnchor" id="author"><a class="anchor" href="#author"></a>Author</h2> - <p>Johannes Ranke</p> + <p>Johannes Ranke and Katrin Lindenberger</p> <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> <pre class="examples"><div class='input'> diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html index 20134030..77f815da 100644 --- a/docs/reference/mmkin.html +++ b/docs/reference/mmkin.html @@ -158,7 +158,10 @@ datasets specified in its first two arguments.</p> cores <span class='op'>=</span> <span class='fu'>parallel</span><span class='fu'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span><span class='op'>(</span><span class='op'>)</span>, cluster <span class='op'>=</span> <span class='cn'>NULL</span>, <span class='va'>...</span> -<span class='op'>)</span></pre> +<span class='op'>)</span> + +<span class='co'># S3 method for mmkin</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, <span class='va'>...</span><span class='op'>)</span></pre> <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> <table class="ref-arguments"> @@ -189,7 +192,11 @@ for parallel execution.</p></td> </tr> <tr> <th>...</th> - <td><p>Further arguments that will be passed to <code><a href='mkinfit.html'>mkinfit</a></code>.</p></td> + <td><p>Not used.</p></td> + </tr> + <tr> + <th>x</th> + <td><p>An mmkin object.</p></td> </tr> </table> @@ -227,9 +234,9 @@ plotting.</p></div> <span class='va'>time_default</span> </div><div class='output co'>#> user system elapsed -#> 4.869 0.357 1.415 </div><div class='input'><span class='va'>time_1</span> +#> 4.634 0.317 1.280 </div><div class='input'><span class='va'>time_1</span> </div><div class='output co'>#> user system elapsed -#> 5.502 0.002 5.507 </div><div class='input'> +#> 5.249 0.016 5.267 </div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>fits.0</span><span class='op'>[[</span><span class='st'>"SFO_lin"</span>, <span class='fl'>2</span><span class='op'>]</span><span class='op'>]</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> parent_M1 parent_sink M1_M2 M1_sink diff --git a/docs/reference/nlme.mmkin-3.png b/docs/reference/nlme.mmkin-3.png Binary files differindex 0b7ce0f6..7c04df4b 100644 --- a/docs/reference/nlme.mmkin-3.png +++ b/docs/reference/nlme.mmkin-3.png diff --git a/docs/reference/nlme.mmkin.html b/docs/reference/nlme.mmkin.html index dd1670fe..2e4f6337 100644 --- a/docs/reference/nlme.mmkin.html +++ b/docs/reference/nlme.mmkin.html @@ -157,7 +157,7 @@ have been obtained by fitting the same model to a list of datasets.</p> data <span class='op'>=</span> <span class='st'>"auto"</span>, fixed <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>as.list</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='fu'><a href='nlme_function.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>model</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>el</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/eval.html'>eval</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/parse.html'>parse</a></span><span class='op'>(</span>text <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='va'>el</span>, <span class='fl'>1</span>, sep <span class='op'>=</span> <span class='st'>"~"</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span><span class='op'>)</span>, - random <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/pdDiag.html'>pdDiag</a></span><span class='op'>(</span><span class='va'>fixed</span><span class='op'>)</span>, + random <span class='op'>=</span> <span class='fu'>pdDiag</span><span class='op'>(</span><span class='va'>fixed</span><span class='op'>)</span>, <span class='va'>groups</span>, start <span class='op'>=</span> <span class='fu'><a href='nlme_function.html'>mean_degparms</a></span><span class='op'>(</span><span class='va'>model</span>, random <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, correlation <span class='op'>=</span> <span class='cn'>NULL</span>, @@ -262,6 +262,12 @@ parameters taken from the mmkin object are used</p></td> <p>Upon success, a fitted 'nlme.mmkin' object, which is an nlme object with additional elements. It also inherits from 'mixed.mmkin'.</p> + <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2> + + <p>Note that the convergence of the nlme algorithms depends on the quality +of the data. In degradation kinetics, we often only have few datasets +(e.g. data for few soils) and complicated degradation models, which may +make it impossible to obtain convergence with nlme.</p> <h2 class="hasAnchor" id="note"><a class="anchor" href="#note"></a>Note</h2> <p>As the object inherits from <a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme::nlme</a>, there is a wealth of @@ -335,16 +341,17 @@ methods that will automatically work on 'nlme.mmkin' objects, such as <span class='co'># f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])</span> <span class='co'>#plot(f_nlme_sfo_sfo_ff)</span> - <span class='co'># With the log-Cholesky parameterization, this converges in 11</span> - <span class='co'># iterations and around 100 seconds, but without tweaking control</span> - <span class='co'># parameters (with pdDiag, increasing the tolerance and pnlsMaxIter was</span> - <span class='co'># necessary)</span> - <span class='va'>f_nlme_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in nlme.formula(model = value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_A1, f_parent_qlogis, log_k1, log_k2, g_qlogis), data = structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L ), .Label = c("1", "2", "3", "4", "5"), class = c("ordered", "factor")), name = c("parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0, 0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2, 96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18, 10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 4.3, 4.6, 7, 7.2, 8.2, 8, 11, 13.7, 11.5, 12.7, 14.9, 14.5, 12.1, 12.3, 9.9, 10.2, 8.8, 7.8, 93.6, 92.3, 87, 82.2, 74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1, 29, 26.5, 27.6, 3.9, 3.1, 6.9, 6.6, 10.4, 8.3, 14.4, 13.7, 22.1, 22.3, 27.5, 25.4, 28, 26.6, 25.8, 25.3, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1, 10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 9.6, 7.7, 15, 15.1, 21.2, 21.1, 19.7, 18.9, 17.5, 15.9, 9.5, 9.8, 6.2, 6.1, 99.8, 98.3, 77.1, 77.2, 59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3, 2.9, 2, 1.8, 2, 2.2, 4.2, 3.9, 7.4, 7.9, 14.5, 13.7, 14.2, 12.2, 13.7, 13.2, 13.6, 15.4, 10.4, 11.6, 10, 9.5, 9.1, 9, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6, 65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3, 3.3, 3.4, 3.9, 2.9, 6.4, 7.2, 9.1, 8.5, 11.7, 12, 13.3, 13.2, 14.3, 12.1)), row.names = c(NA, -170L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = value ~ time | ds, FUN = function (x) max(x, na.rm = TRUE), order.groups = FALSE), start = list( fixed = c(parent_0 = 93.8101519326534, log_k_A1 = -9.76474551635931, f_parent_qlogis = -0.971114801595408, log_k1 = -1.87993711571859, log_k2 = -4.27081421366622, g_qlogis = 0.135644115277507 ), random = list(ds = structure(c(2.56569977430371, -3.49441920289139, -3.32614443321494, 4.35347873814922, -0.0986148763466161, 4.65850590018027, 1.8618544764481, 6.12693257601545, 4.91792724701579, -17.5652201996596, -0.466203822618637, 0.746660653597927, 0.282193987271096, -0.42053488943072, -0.142115928819667, 0.369240076779088, -1.38985563501659, 1.02592753494098, 0.73090914081534, -0.736221117518819, 0.768170629350299, -1.89347658079869, 1.72168783460352, 0.844607177798114, -1.44098906095325, -0.377731855445672, 0.168180098477565, 0.469683412912104, 0.500717664434525, -0.760849320378522), .Dim = 5:6, .Dimnames = list(c("1", "2", "3", "4", "5"), c("parent_0", "log_k_A1", "f_parent_qlogis", "log_k1", "log_k2", "g_qlogis"))))), fixed = list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), random = structure(numeric(0), class = c("pdDiag", "pdMat"), formula = structure(list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), class = "listForm"), Dimnames = list(NULL, NULL))): maximum number of iterations (maxIter = 50) reached without convergence</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 48.39 16.98 43</span></div><div class='input'> + <span class='co'># For the following, we need to increase pnlsMaxIter and the tolerance</span> + <span class='co'># to get convergence</span> + <span class='va'>f_nlme_dfop_sfo</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, + control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>120</span>, tolerance <span class='op'>=</span> <span class='fl'>5e-4</span><span class='op'>)</span><span class='op'>)</span> + <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in plot(f_nlme_dfop_sfo): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +</div><div class='img'><img src='nlme.mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +</div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value +#> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274 +#> f_nlme_sfo_sfo 2 9 1085.1821 1113.4043 -533.5910 1 vs 2 249.3274 <.0001</div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span> </div><div class='output co'>#> $ff #> parent_sink parent_A1 A1_sink @@ -355,7 +362,15 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> parent 19.13518 63.5657 #> A1 66.02155 219.3189 #> </div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in endpoints(f_nlme_dfop_sfo): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +</div><div class='output co'>#> $ff +#> parent_A1 parent_sink +#> 0.2768574 0.7231426 +#> +#> $distimes +#> DT50 DT90 DT50back DT50_k1 DT50_k2 +#> parent 11.07091 104.6320 31.49738 4.462384 46.20825 +#> A1 162.30523 539.1663 NA NA NA +#> </div><div class='input'> <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='fu'>findFunction</span><span class='op'>(</span><span class='st'>"varConstProp"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>></span> <span class='fl'>0</span><span class='op'>)</span> <span class='op'>{</span> <span class='co'># tc error model for nlme available</span> <span class='co'># Attempts to fit metabolite kinetics with the tc error model are possible,</span> <span class='co'># but need tweeking of control values and sometimes do not converge</span> @@ -396,9 +411,7 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> Parameter estimates: #> const prop #> 2.23224114 0.01262341 </div><div class='input'> - <span class='va'>f_2_obs</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>m_sfo_sfo</span>, - <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>m_dfop_sfo</span><span class='op'>)</span>, - <span class='va'>ds_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> + <span class='va'>f_2_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_2</span>, error_model <span class='op'>=</span> <span class='st'>"obs"</span><span class='op'>)</span> <span class='va'>f_nlme_sfo_sfo_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_obs</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo_obs</span><span class='op'>)</span> </div><div class='output co'>#> Kinetic nonlinear mixed-effects model fit by maximum likelihood @@ -429,18 +442,21 @@ methods that will automatically work on 'nlme.mmkin' objects, such as #> Formula: ~1 | name #> Parameter estimates: #> parent A1 -#> 1.0000000 0.2050003 </div><div class='input'> <span class='va'>f_nlme_dfop_sfo_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_obs</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in nlme.formula(model = value ~ (mkin::get_deg_func())(name, time, parent_0, log_k_A1, f_parent_qlogis, log_k1, log_k2, g_qlogis), data = structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L ), .Label = c("1", "2", "3", "4", "5"), class = c("ordered", "factor")), name = c("parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1", "A1"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0, 0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2, 96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18, 10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 4.3, 4.6, 7, 7.2, 8.2, 8, 11, 13.7, 11.5, 12.7, 14.9, 14.5, 12.1, 12.3, 9.9, 10.2, 8.8, 7.8, 93.6, 92.3, 87, 82.2, 74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1, 29, 26.5, 27.6, 3.9, 3.1, 6.9, 6.6, 10.4, 8.3, 14.4, 13.7, 22.1, 22.3, 27.5, 25.4, 28, 26.6, 25.8, 25.3, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1, 10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 9.6, 7.7, 15, 15.1, 21.2, 21.1, 19.7, 18.9, 17.5, 15.9, 9.5, 9.8, 6.2, 6.1, 99.8, 98.3, 77.1, 77.2, 59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3, 2.9, 2, 1.8, 2, 2.2, 4.2, 3.9, 7.4, 7.9, 14.5, 13.7, 14.2, 12.2, 13.7, 13.2, 13.6, 15.4, 10.4, 11.6, 10, 9.5, 9.1, 9, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6, 65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3, 3.3, 3.4, 3.9, 2.9, 6.4, 7.2, 9.1, 8.5, 11.7, 12, 13.3, 13.2, 14.3, 12.1)), row.names = c(NA, -170L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = value ~ time | ds, FUN = function (x) max(x, na.rm = TRUE), order.groups = FALSE), start = list( fixed = c(parent_0 = 93.4272167134207, log_k_A1 = -9.71590717106959, f_parent_qlogis = -0.953712099744438, log_k1 = -1.95256957646888, log_k2 = -4.42919226610318, g_qlogis = 0.193023137298073 ), random = list(ds = structure(c(2.85557330683041, -3.87630303729395, -2.78062140212751, 4.82042042600536, -1.01906929341432, 4.613992019697, 2.05871276943309, 6.0766404049189, 4.86471337131288, -17.6140585653619, -0.480721175257541, 0.773079218835614, 0.260464433006093, -0.440615012802434, -0.112207463781733, 0.445812953745225, -1.49588630006094, 1.13602040717272, 0.801850880762046, -0.887797941619048, 0.936480292463262, -2.43093808171905, 1.91256225793793, 0.984827519864443, -1.40293198854659, -0.455176326336681, 0.376355651864385, 0.343919720700401, 0.46329187713133, -0.728390923359434 ), .Dim = 5:6, .Dimnames = list(c("1", "2", "3", "4", "5"), c("parent_0", "log_k_A1", "f_parent_qlogis", "log_k1", "log_k2", "g_qlogis"))))), fixed = list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), random = structure(numeric(0), class = c("pdDiag", "pdMat"), formula = structure(list(parent_0 ~ 1, log_k_A1 ~ 1, f_parent_qlogis ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1), class = "listForm"), Dimnames = list(NULL, NULL)), weights = structure(numeric(0), formula = ~1 | name, class = c("varIdent", "varFunc"))): maximum number of iterations (maxIter = 50) reached without convergence</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 58.24 16.62 52.48</span></div><div class='input'> - <span class='va'>f_2_tc</span> <span class='op'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>m_sfo_sfo</span>, - <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>m_dfop_sfo</span><span class='op'>)</span>, - <span class='va'>ds_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> - <span class='co'># f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # stops with error message</span> - <span class='va'>f_nlme_dfop_sfo_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_tc</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='warning'>Warning: longer object length is not a multiple of shorter object length</span></div><div class='output co'>#> <span class='error'>Error in X[, fmap[[nm]]] <- gradnm: number of items to replace is not a multiple of replacement length</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 6.327 2.686 5.428</span></div><div class='input'> <span class='co'># We get warnings about false convergence in the LME step in several iterations</span> - <span class='co'># but as the last such warning occurs in iteration 25 and we have 28 iterations</span> - <span class='co'># we can ignore these</span> - <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_dfop_sfo_obs</span>, <span class='va'>f_nlme_dfop_sfo_tc</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs, f_nlme_dfop_sfo_tc): object 'f_nlme_dfop_sfo' not found</span></div><div class='input'> +#> 1.0000000 0.2050003 </div><div class='input'> <span class='va'>f_nlme_dfop_sfo_obs</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2_obs</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>, + control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>120</span>, tolerance <span class='op'>=</span> <span class='fl'>5e-4</span><span class='op'>)</span><span class='op'>)</span> + + <span class='va'>f_2_tc</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_2</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span> + <span class='co'># f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations</span> + <span class='co'># f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ],</span> + <span class='co'># control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm</span> + + <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_dfop_sfo_obs</span><span class='op'>)</span> +</div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio +#> f_nlme_dfop_sfo 1 13 843.8547 884.6201 -408.9274 +#> f_nlme_dfop_sfo_obs 2 14 817.5338 861.4350 -394.7669 1 vs 2 28.32089 +#> p-value +#> f_nlme_dfop_sfo +#> f_nlme_dfop_sfo_obs <.0001</div><div class='input'> <span class='co'># }</span> </div></pre> </div> diff --git a/docs/reference/transform_odeparms.html b/docs/reference/transform_odeparms.html index efaf7b46..e2cb876b 100644 --- a/docs/reference/transform_odeparms.html +++ b/docs/reference/transform_odeparms.html @@ -77,7 +77,7 @@ the ilr transformation is used." /> </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.0.1</span> </span> </div> @@ -231,50 +231,64 @@ This is no problem for the internal use in <a href='mkinfit.html'>mkinfit</a>.</ <pre class="examples"><div class='input'> <span class='va'>SFO_SFO</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span>, sink <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, - m1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'><span class='co'># Fit the model to the FOCUS example dataset D using defaults</span> -<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> + m1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"min"</span><span class='op'>)</span> +</div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> +<span class='co'># Fit the model to the FOCUS example dataset D using defaults</span> +<span class='va'>FOCUS_D</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>FOCUS_2006_D</span>, <span class='va'>value</span> <span class='op'>!=</span> <span class='fl'>0</span><span class='op'>)</span> <span class='co'># remove zero values to avoid warning</span> +<span class='va'>fit</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>)</span> <span class='co'># Transformed and backtransformed parameters</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> Estimate Std. Error Lower Upper -#> parent_0 99.5985 1.5702 96.404 102.79 -#> log_k_parent -2.3157 0.0409 -2.399 -2.23 -#> log_k_m1 -5.2475 0.1332 -5.518 -4.98 -#> f_parent_qlogis 0.0579 0.0893 -0.124 0.24 -#> sigma 3.1255 0.3585 2.396 3.85</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower Upper -#> parent_0 99.59848 1.57022 63.43 2.30e-36 96.40383 102.7931 -#> k_parent 0.09870 0.00403 24.47 4.96e-23 0.09082 0.1073 -#> k_m1 0.00526 0.00070 7.51 6.16e-09 0.00401 0.0069 -#> f_parent_to_m1 0.51448 0.02230 23.07 3.10e-22 0.46912 0.5596 -#> sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.8549</div><div class='input'> +</div><div class='output co'>#> Estimate Std. Error Lower Upper +#> parent_0 99.60 1.5702 96.40 102.79 +#> log_k_parent_sink -3.04 0.0763 -3.19 -2.88 +#> log_k_parent_m1 -2.98 0.0403 -3.06 -2.90 +#> log_k_m1_sink -5.25 0.1332 -5.52 -4.98 +#> sigma 3.13 0.3585 2.40 3.85</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower Upper +#> parent_0 99.59848 1.57022 63.43 2.30e-36 96.40384 102.7931 +#> k_parent_sink 0.04792 0.00365 13.11 6.13e-15 0.04103 0.0560 +#> k_parent_m1 0.05078 0.00205 24.80 3.27e-23 0.04678 0.0551 +#> k_m1_sink 0.00526 0.00070 7.51 6.16e-09 0.00401 0.0069 +#> sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.8549</div><div class='input'> <span class='co'># \dontrun{</span> -<span class='co'># Compare to the version without transforming rate parameters</span> -<span class='va'>fit.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_2006_D</span>, transform_rates <span class='op'>=</span> <span class='cn'>FALSE</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#> <span class='error'>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</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0.003 0 0.003</span></div><div class='input'><span class='va'>fit.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.2</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in summary(fit.2): object 'fit.2' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in print(fit.2.s$par, 3): object 'fit.2.s' not found</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='error'>Error in print(fit.2.s$bpar, 3): object 'fit.2.s' not found</span></div><div class='input'><span class='co'># }</span> +<span class='co'># Compare to the version without transforming rate parameters (does not work</span> +<span class='co'># with analytical solution, we get NA values for m1 in predictions)</span> +<span class='va'>fit.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO</span>, <span class='va'>FOCUS_D</span>, transform_rates <span class='op'>=</span> <span class='cn'>FALSE</span>, + solution_type <span class='op'>=</span> <span class='st'>"deSolve"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.2</span><span class='op'>)</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> Estimate Std. Error Lower Upper +#> parent_0 99.59849 1.57022 96.40385 1.03e+02 +#> k_parent_sink 0.04792 0.00365 0.04049 5.54e-02 +#> k_parent_m1 0.05078 0.00205 0.04661 5.49e-02 +#> k_m1_sink 0.00526 0.00070 0.00384 6.69e-03 +#> sigma 3.12550 0.35852 2.39609 3.85e+00</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.2.s</span><span class='op'>$</span><span class='va'>bpar</span>, <span class='fl'>3</span><span class='op'>)</span> +</div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower Upper +#> parent_0 99.59849 1.57022 63.43 2.30e-36 96.40385 1.03e+02 +#> k_parent_sink 0.04792 0.00365 13.11 6.13e-15 0.04049 5.54e-02 +#> k_parent_m1 0.05078 0.00205 24.80 3.27e-23 0.04661 5.49e-02 +#> k_m1_sink 0.00526 0.00070 7.51 6.16e-09 0.00384 6.69e-03 +#> sigma 3.12550 0.35852 8.72 2.24e-10 2.39609 3.85e+00</div><div class='input'><span class='co'># }</span> <span class='va'>initials</span> <span class='op'><-</span> <span class='va'>fit</span><span class='op'>$</span><span class='va'>start</span><span class='op'>$</span><span class='va'>value</span> <span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>initials</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>start</span><span class='op'>)</span> <span class='va'>transformed</span> <span class='op'><-</span> <span class='va'>fit</span><span class='op'>$</span><span class='va'>start_transformed</span><span class='op'>$</span><span class='va'>value</span> <span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>transformed</span><span class='op'>)</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/colnames.html'>rownames</a></span><span class='op'>(</span><span class='va'>fit</span><span class='op'>$</span><span class='va'>start_transformed</span><span class='op'>)</span> <span class='fu'>transform_odeparms</span><span class='op'>(</span><span class='va'>initials</span>, <span class='va'>SFO_SFO</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 log_k_parent log_k_m1 f_parent_qlogis -#> 100.750000 -2.302585 -2.301586 0.000000 </div><div class='input'><span class='fu'>backtransform_odeparms</span><span class='op'>(</span><span class='va'>transformed</span>, <span class='va'>SFO_SFO</span><span class='op'>)</span> -</div><div class='output co'>#> parent_0 k_parent k_m1 f_parent_to_m1 -#> 100.7500 0.1000 0.1001 0.5000 </div><div class='input'> +</div><div class='output co'>#> parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink +#> 100.750000 -2.302585 -2.301586 -2.300587 </div><div class='input'><span class='fu'>backtransform_odeparms</span><span class='op'>(</span><span class='va'>transformed</span>, <span class='va'>SFO_SFO</span><span class='op'>)</span> +</div><div class='output co'>#> parent_0 k_parent_sink k_parent_m1 k_m1_sink +#> 100.7500 0.1000 0.1001 0.1002 </div><div class='input'> <span class='co'># \dontrun{</span> -<span class='co'># The case of formation fractions</span> +<span class='co'># The case of formation fractions (this is now the default)</span> <span class='va'>SFO_SFO.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span> parent <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span>, to <span class='op'>=</span> <span class='st'>"m1"</span>, sink <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>, m1 <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>type <span class='op'>=</span> <span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> -<span class='va'>fit.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit.ff.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff</span><span class='op'>)</span> +<span class='va'>fit.ff</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.ff.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.ff.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> </div><div class='output co'>#> Estimate Std. Error Lower Upper #> parent_0 99.5985 1.5702 96.404 102.79 @@ -299,8 +313,8 @@ This is no problem for the internal use in <a href='mkinfit.html'>mkinfit</a>.</ use_of_ff <span class='op'>=</span> <span class='st'>"max"</span><span class='op'>)</span> </div><div class='output co'>#> <span class='message'>Temporary DLL for differentials generated and loaded</span></div><div class='input'> -<span class='va'>fit.ff.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff.2</span>, <span class='va'>FOCUS_2006_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> -</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='va'>fit.ff.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff.2</span><span class='op'>)</span> +<span class='va'>fit.ff.2</span> <span class='op'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span><span class='op'>(</span><span class='va'>SFO_SFO.ff.2</span>, <span class='va'>FOCUS_D</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span> +<span class='va'>fit.ff.2.s</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>fit.ff.2</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>fit.ff.2.s</span><span class='op'>$</span><span class='va'>par</span>, <span class='fl'>3</span><span class='op'>)</span> </div><div class='output co'>#> Estimate Std. Error Lower Upper #> parent_0 84.79 3.012 78.67 90.91 diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 7e3d8a53..601a4464 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -175,9 +175,6 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/plot.nafta.html</loc> </url> <url> - <loc>https://pkgdown.jrwb.de/mkin/reference/print.mmkin.html</loc> - </url> - <url> <loc>https://pkgdown.jrwb.de/mkin/reference/reexports.html</loc> </url> <url> diff --git a/man/confint.mkinfit.Rd b/man/confint.mkinfit.Rd index fd2890ff..b19e78c2 100644 --- a/man/confint.mkinfit.Rd +++ b/man/confint.mkinfit.Rd @@ -82,20 +82,20 @@ confint(f, method = "profile") if (identical(Sys.getenv("NOT_CRAN"), "true")) { n_cores <- parallel::detectCores() - 1 } else { - n_cores <- 1 + 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 <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), + use_of_ff = "min", 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)) # 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 +# minor interest), we get a nice performance improvement if we use at least 4 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)) ci_profile diff --git a/man/logLik.mkinfit.Rd b/man/logLik.mkinfit.Rd index 637570e4..6b40305e 100644 --- a/man/logLik.mkinfit.Rd +++ b/man/logLik.mkinfit.Rd @@ -35,10 +35,10 @@ and the fitted error model parameters. parent = mkinsub("SFO", to = "m1"), m1 = mkinsub("SFO") ) - d_t <- FOCUS_2006_D + d_t <- subset(FOCUS_2006_D, value != 0) f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity) - f_obs <- mkinfit(sfo_sfo, d_t, error_model = "obs", quiet = TRUE) - f_tc <- mkinfit(sfo_sfo, d_t, error_model = "tc", quiet = TRUE) + f_obs <- update(f_nw, error_model = "obs") + f_tc <- update(f_nw, error_model = "tc") AIC(f_nw, f_obs, f_tc) } diff --git a/man/mkinresplot.Rd b/man/mkinresplot.Rd index 498d914d..9658ddb5 100644 --- a/man/mkinresplot.Rd +++ b/man/mkinresplot.Rd @@ -75,5 +75,5 @@ lines of the mkinfit object, and \code{\link{plot_res}} for a function combining the plot of the fit and the residual plot. } \author{ -Johannes Ranke +Johannes Ranke and Katrin Lindenberger } diff --git a/man/mmkin.Rd b/man/mmkin.Rd index 9b836242..170ce8df 100644 --- a/man/mmkin.Rd +++ b/man/mmkin.Rd @@ -2,6 +2,7 @@ % Please edit documentation in R/mmkin.R \name{mmkin} \alias{mmkin} +\alias{print.mmkin} \title{Fit one or more kinetic models with one or more state variables to one or more datasets} \usage{ @@ -12,6 +13,8 @@ mmkin( cluster = NULL, ... ) + +\method{print}{mmkin}(x, ...) } \arguments{ \item{models}{Either a character vector of shorthand names like @@ -30,7 +33,9 @@ detected by \code{\link[parallel:detectCores]{parallel::detectCores()}} are used \item{cluster}{A cluster as returned by \code{\link{makeCluster}} to be used for parallel execution.} -\item{\dots}{Further arguments that will be passed to \code{\link{mkinfit}}.} +\item{\dots}{Not used.} + +\item{x}{An \link{mmkin} object.} } \value{ A two-dimensional \code{\link{array}} of \code{\link{mkinfit}} diff --git a/man/nlme.mmkin.Rd b/man/nlme.mmkin.Rd index f78256ac..2fb0488a 100644 --- a/man/nlme.mmkin.Rd +++ b/man/nlme.mmkin.Rd @@ -79,6 +79,12 @@ This functions sets up a nonlinear mixed effects model for an mmkin row object. An mmkin row object is essentially a list of mkinfit objects that have been obtained by fitting the same model to a list of datasets. } +\details{ +Note that the convergence of the nlme algorithms depends on the quality +of the data. In degradation kinetics, we often only have few datasets +(e.g. data for few soils) and complicated degradation models, which may +make it impossible to obtain convergence with nlme. +} \note{ As the object inherits from \link[nlme:nlme]{nlme::nlme}, there is a wealth of methods that will automatically work on 'nlme.mmkin' objects, such as @@ -120,11 +126,10 @@ f_nlme_sfo <- nlme(f["SFO", ]) # f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ]) #plot(f_nlme_sfo_sfo_ff) - # With the log-Cholesky parameterization, this converges in 11 - # iterations and around 100 seconds, but without tweaking control - # parameters (with pdDiag, increasing the tolerance and pnlsMaxIter was - # necessary) - f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ]) + # For the following, we need to increase pnlsMaxIter and the tolerance + # to get convergence + f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ], + control = list(pnlsMaxIter = 120, tolerance = 5e-4)) plot(f_nlme_dfop_sfo) @@ -144,22 +149,18 @@ f_nlme_sfo <- nlme(f["SFO", ]) print(f_nlme_dfop_tc) } - f_2_obs <- mmkin(list("SFO-SFO" = m_sfo_sfo, - "DFOP-SFO" = m_dfop_sfo), - ds_2, quiet = TRUE, error_model = "obs") + f_2_obs <- update(f_2, error_model = "obs") f_nlme_sfo_sfo_obs <- nlme(f_2_obs["SFO-SFO", ]) print(f_nlme_sfo_sfo_obs) - f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ]) + f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ], + control = list(pnlsMaxIter = 120, tolerance = 5e-4)) - f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo, - "DFOP-SFO" = m_dfop_sfo), - ds_2, quiet = TRUE, error_model = "tc") - # f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # stops with error message - f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ]) - # We get warnings about false convergence in the LME step in several iterations - # but as the last such warning occurs in iteration 25 and we have 28 iterations - # we can ignore these - anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs, f_nlme_dfop_sfo_tc) + f_2_tc <- update(f_2, error_model = "tc") + # f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations + # f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ], + # control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm + + anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs) } } diff --git a/man/print.mmkin.Rd b/man/print.mmkin.Rd deleted file mode 100644 index 29abe143..00000000 --- a/man/print.mmkin.Rd +++ /dev/null @@ -1,16 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/mmkin.R -\name{print.mmkin} -\alias{print.mmkin} -\title{Print method for mmkin objects} -\usage{ -\method{print}{mmkin}(x, ...) -} -\arguments{ -\item{x}{An \link{mmkin} object.} - -\item{\dots}{Not used.} -} -\description{ -Print method for mmkin objects -} diff --git a/man/transform_odeparms.Rd b/man/transform_odeparms.Rd index f38bb051..3a97ff8d 100644 --- a/man/transform_odeparms.Rd +++ b/man/transform_odeparms.Rd @@ -69,17 +69,21 @@ This is no problem for the internal use in \link{mkinfit}. SFO_SFO <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), - m1 = list(type = "SFO")) + m1 = list(type = "SFO"), use_of_ff = "min") + # Fit the model to the FOCUS example dataset D using defaults -fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE) +FOCUS_D <- subset(FOCUS_2006_D, value != 0) # remove zero values to avoid warning +fit <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE) fit.s <- summary(fit) # Transformed and backtransformed parameters print(fit.s$par, 3) print(fit.s$bpar, 3) \dontrun{ -# Compare to the version without transforming rate parameters -fit.2 <- mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates = FALSE, quiet = TRUE) +# Compare to the version without transforming rate parameters (does not work +# with analytical solution, we get NA values for m1 in predictions) +fit.2 <- mkinfit(SFO_SFO, FOCUS_D, transform_rates = FALSE, + solution_type = "deSolve", quiet = TRUE) fit.2.s <- summary(fit.2) print(fit.2.s$par, 3) print(fit.2.s$bpar, 3) @@ -93,13 +97,13 @@ transform_odeparms(initials, SFO_SFO) backtransform_odeparms(transformed, SFO_SFO) \dontrun{ -# The case of formation fractions +# The case of formation fractions (this is now the default) SFO_SFO.ff <- mkinmod( parent = list(type = "SFO", to = "m1", sink = TRUE), m1 = list(type = "SFO"), use_of_ff = "max") -fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE) +fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_D, quiet = TRUE) fit.ff.s <- summary(fit.ff) print(fit.ff.s$par, 3) print(fit.ff.s$bpar, 3) @@ -114,7 +118,7 @@ SFO_SFO.ff.2 <- mkinmod( use_of_ff = "max") -fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D, quiet = TRUE) +fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_D, quiet = TRUE) fit.ff.2.s <- summary(fit.ff.2) print(fit.ff.2.s$par, 3) print(fit.ff.2.s$bpar, 3) @@ -21,7 +21,7 @@ Testing mkin ✔ | 8 | mkinmod model generation and printing [0.2 s] ✔ | 3 | Model predictions with mkinpredict [0.4 s] ✔ | 16 | Evaluations according to 2015 NAFTA guidance [1.6 s] -✔ | 9 | Nonlinear mixed-effects models [7.7 s] +✔ | 9 | Nonlinear mixed-effects models [7.8 s] ✔ | 14 | Plotting [1.7 s] ✔ | 4 | Residuals extracted from mkinfit models ✔ | 2 | Complex test case from Schaefer et al. (2007) Piacenza paper [1.5 s] @@ -32,6 +32,6 @@ Testing mkin ✔ | 4 | Calculation of maximum time weighted average concentrations (TWAs) [2.4 s] ══ Results ═════════════════════════════════════════════════════════════════════ -Duration: 40.4 s +Duration: 40.6 s [ FAIL 0 | WARN 0 | SKIP 0 | PASS 176 ] |
