From af7c6de4db9981ac814362c441fbac22c8faa2d7 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 24 Nov 2022 09:02:26 +0100 Subject: Start online docs of the development version --- docs/dev/reference/Rplot001.png | Bin 22432 -> 14083 bytes 1 file changed, 0 insertions(+), 0 deletions(-) (limited to 'docs/dev/reference/Rplot001.png') diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png index b3448db0..ca982688 100644 Binary files a/docs/dev/reference/Rplot001.png and b/docs/dev/reference/Rplot001.png differ -- cgit v1.2.3 From 9a1136dc5550663b352239502a39a07601959644 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 2 Dec 2022 08:00:40 +0100 Subject: Update online docs --- docs/dev/news/index.html | 4 +- docs/dev/pkgdown.yml | 2 +- docs/dev/reference/Rplot001.png | Bin 14083 -> 18113 bytes docs/dev/reference/Rplot002.png | Bin 13699 -> 38732 bytes docs/dev/reference/mhmkin-1.png | Bin 0 -> 53169 bytes docs/dev/reference/mhmkin-2.png | Bin 0 -> 113443 bytes docs/dev/reference/mhmkin.html | 103 +++++++++++++++++++++++++++++++++++----- 7 files changed, 95 insertions(+), 14 deletions(-) create mode 100644 docs/dev/reference/mhmkin-1.png create mode 100644 docs/dev/reference/mhmkin-2.png (limited to 'docs/dev/reference/Rplot001.png') diff --git a/docs/dev/news/index.html b/docs/dev/news/index.html index 50afb3e9..c9663964 100644 --- a/docs/dev/news/index.html +++ b/docs/dev/news/index.html @@ -89,7 +89,9 @@

mkin 1.2.2

-
+

mkin 1.2.1 (2022-11-19)

  • ‘{data,R}/ds_mixed.rda’: Include the test data in the package instead of generating it in ‘tests/testthat/setup_script.R’. Refactor the generating code to make it consistent and update tests.

    • diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml index 0669ac9c..33252d6f 100644 --- a/docs/dev/pkgdown.yml +++ b/docs/dev/pkgdown.yml @@ -13,7 +13,7 @@ articles: dimethenamid_2018: web_only/dimethenamid_2018.html multistart: web_only/multistart.html saem_benchmarks: web_only/saem_benchmarks.html -last_built: 2022-11-24T06:50Z +last_built: 2022-12-02T06:58Z urls: reference: https://pkgdown.jrwb.de/mkin/reference article: https://pkgdown.jrwb.de/mkin/articles diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png index ca982688..8a77fc7f 100644 Binary files a/docs/dev/reference/Rplot001.png and b/docs/dev/reference/Rplot001.png differ diff --git a/docs/dev/reference/Rplot002.png b/docs/dev/reference/Rplot002.png index de2d61aa..c1621707 100644 Binary files a/docs/dev/reference/Rplot002.png and b/docs/dev/reference/Rplot002.png differ diff --git a/docs/dev/reference/mhmkin-1.png b/docs/dev/reference/mhmkin-1.png new file mode 100644 index 00000000..2ecb6759 Binary files /dev/null and b/docs/dev/reference/mhmkin-1.png differ diff --git a/docs/dev/reference/mhmkin-2.png b/docs/dev/reference/mhmkin-2.png new file mode 100644 index 00000000..9bb43d35 Binary files /dev/null and b/docs/dev/reference/mhmkin-2.png differ diff --git a/docs/dev/reference/mhmkin.html b/docs/dev/reference/mhmkin.html index e72d17f9..1328aa48 100644 --- a/docs/dev/reference/mhmkin.html +++ b/docs/dev/reference/mhmkin.html @@ -113,7 +113,6 @@ mhmkin( backend = "saemix", algorithm = "saem", no_random_effect = NULL, - auto_ranef_threshold = 3, ..., cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(), cluster = NULL @@ -150,16 +149,14 @@ supported

    no_random_effect
    -

    Default is NULL and will be passed to saem. If -you specify "auto", random effects are only included if the number -of datasets in which the parameter passed the t-test is at least 'auto_ranef_threshold'. -Beware that while this may make for convenient model reduction or even -numerical stability of the algorithm, it will likely lead to -underparameterised models.

    - - -
    auto_ranef_threshold
    -

    See 'no_random_effect.

    +

    Default is NULL and will be passed to saem. If a +character vector is supplied, it will be passed to all calls to saem, +which will exclude random effects for all matching parameters. Alternatively, +a list of character vectors or an object of class illparms.mhmkin can be +specified. They have to have the same dimensions that the return object of +the current call will have, i.e. the number of rows must match the number +of degradation models in the mmkin object(s), and the number of columns must +match the number of error models used in the mmkin object(s).

    cores
    @@ -203,7 +200,7 @@ and the error model names for the second index (column index), with class attribute 'mhmkin'.

    -

    An object of class mhmkin.

    +

    An object inheriting from mhmkin.

See also

@@ -214,6 +211,88 @@ attribute 'mhmkin'.

Johannes Ranke

+
+

Examples

+ 
# \dontrun{
+# We start with separate evaluations of all the first six datasets with two
+# degradation models and two error models
+f_sep_const <- mmkin(c("SFO", "FOMC"), ds_fomc[1:6], cores = 2, quiet = TRUE)
+f_sep_tc <- update(f_sep_const, error_model = "tc")
+# The mhmkin function sets up hierarchical degradation models aka
+# nonlinear mixed-effects models for all four combinations, specifying
+# uncorrelated random effects for all degradation parameters
+f_saem_1 <- mhmkin(list(f_sep_const, f_sep_tc), cores = 2)
+status(f_saem_1)
+#>            error
+#> degradation const tc
+#>        SFO  OK    OK
+#>        FOMC OK    OK
+#> 
+#> OK: Fit terminated successfully
+# The 'illparms' function shows that in all hierarchical fits, at least
+# one random effect is ill-defined (the confidence interval for the
+# random effect expressed as standard deviation includes zero)
+illparms(f_saem_1)
+#>            error
+#> degradation const        tc                        
+#>        SFO  sd(parent_0) sd(parent_0)              
+#>        FOMC sd(log_beta) sd(parent_0), sd(log_beta)
+# Therefore we repeat the fits, excluding the ill-defined random effects
+f_saem_2 <- update(f_saem_1, no_random_effect = illparms(f_saem_1))
+status(f_saem_2)
+#>            error
+#> degradation const tc
+#>        SFO  OK    OK
+#>        FOMC OK    OK
+#> 
+#> OK: Fit terminated successfully
+illparms(f_saem_2)
+#>            error
+#> degradation const tc
+#>        SFO          
+#>        FOMC         
+# Model comparisons show that FOMC with two-component error is preferable,
+# and confirms our reduction of the default parameter model
+anova(f_saem_1)
+#> Data: 95 observations of 1 variable(s) grouped in 6 datasets
+#> 
+#>            npar    AIC    BIC     Lik
+#> SFO const     5 574.40 573.35 -282.20
+#> SFO tc        6 543.72 542.47 -265.86
+#> FOMC const    7 489.67 488.22 -237.84
+#> FOMC tc       8 406.11 404.44 -195.05
+anova(f_saem_2)
+#> Data: 95 observations of 1 variable(s) grouped in 6 datasets
+#> 
+#>            npar    AIC    BIC     Lik
+#> SFO const     4 572.22 571.39 -282.11
+#> SFO tc        5 541.63 540.59 -265.81
+#> FOMC const    6 487.38 486.13 -237.69
+#> FOMC tc       6 402.12 400.88 -195.06
+# The convergence plot for the selected model looks fine
+saemix::plot(f_saem_2[["FOMC", "tc"]]$so, plot.type = "convergence")
+
+# The plot of predictions versus data shows that we have a pretty data-rich
+# situation with homogeneous distribution of residuals, because we used the
+# same degradation model, error model and parameter distribution model that
+# was used in the data generation.
+plot(f_saem_2[["FOMC", "tc"]])
+
+# We can specify the same parameter model reductions manually
+no_ranef <- list("parent_0", "log_beta", "parent_0", c("parent_0", "log_beta"))
+dim(no_ranef) <- c(2, 2)
+f_saem_2m <- update(f_saem_1, no_random_effect = no_ranef)
+anova(f_saem_2m)
+#> Data: 95 observations of 1 variable(s) grouped in 6 datasets
+#> 
+#>            npar    AIC    BIC     Lik
+#> SFO const     4 572.22 571.39 -282.11
+#> SFO tc        5 541.63 540.59 -265.81
+#> FOMC const    6 487.38 486.13 -237.69
+#> FOMC tc       6 402.12 400.88 -195.06
+# }
+
+
diff --git a/docs/dev/news/index.html b/docs/dev/news/index.html index e2b44bf5..6127ebc6 100644 --- a/docs/dev/news/index.html +++ b/docs/dev/news/index.html @@ -90,7 +90,11 @@

mkin 1.2.2

  • ‘R/mhmkin.R’: Allow an ‘illparms.mhmkin’ object or a list with suitable dimensions as value of the argument ‘no_random_effects’, making it possible to exclude random effects that were ill-defined in simpler variants of the set of degradation models. Remove the possibility to exclude random effects based on separate fits, as it did not work well.

    • -

  • ‘R/summary.saem.mmkin.R’: List all initial parameter values in the summary, including random effects and error model parameters. Avoid redundant warnings that occurred in the calculation of correlations of the fixed effects in the case that the Fisher information matrix could not be inverted.

    • +

  • ‘R/summary.saem.mmkin.R’: List all initial parameter values in the summary, including random effects and error model parameters. Avoid redundant warnings that occurred in the calculation of correlations of the fixed effects in the case that the Fisher information matrix could not be inverted. List correlations of random effects if specified by the user in the covariance model.

    • +

  • ‘R/parplot.R’: Possibility to select the top ‘llquant’ fraction of the fits for the parameter plots, and improved legend text.

    • +

  • ‘R/illparms.R’: Also check if confidence intervals for slope parameters in covariate models include zero. Only implemented for fits obtained with the saemix backend.

    • +

  • ‘R/parplot.R’: Make the function work also in the case that some of the multistart runs failed.

    • +

  • ‘R/intervals.R’: Include correlations of random effects in the model in case there are any.

mkin 1.2.1 (2022-11-19)

@@ -140,7 +144,8 @@

mkin 1.0.5 (2021-09-15)

-
  • ‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”
+
  • ‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”
    • +

mkin 1.0.4 (2021-04-20)

  • All plotting functions setting graphical parameters: Use on.exit() for resetting graphical parameters

    • @@ -149,10 +154,12 @@

mkin 1.0.3 (2021-02-15)

-
  • Review and update README, the ‘Introduction to mkin’ vignette and some of the help pages
+

mkin 1.0.2 (Unreleased)

-
  • ‘mkinfit’: Keep model names stored in ‘mkinmod’ objects, avoiding their loss in ‘gmkin’
+

mkin 1.0.1 (2021-02-10)

  • ‘confint.mmkin’, ‘nlme.mmkin’, ‘transform_odeparms’: Fix example code in dontrun sections that failed with current defaults

    • @@ -207,7 +214,8 @@

mkin 0.9.49.11 (2020-04-20)

-
  • Increase a test tolerance to make it pass on all CRAN check machines
+

mkin 0.9.49.10 (2020-04-18)

  • ‘nlme.mmkin’: An nlme method for mmkin row objects and an associated S3 class with print, plot, anova and endpoint methods

    • @@ -322,7 +330,8 @@

mkin 0.9.46 (2017-07-24)

-
  • Remove test_FOMC_ill-defined.R as it is too platform dependent
+

mkin 0.9.45.2 (2017-07-24)

  • Rename twa to max_twa_parent to avoid conflict with twa from my pfm package

    • @@ -334,7 +343,8 @@

    mkin 0.9.45.1 (2016-12-20)

    New features

    -
    • A twa function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).
    +
    • A twa function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).
      • +

mkin 0.9.45 (2016-12-08)

@@ -349,7 +359,8 @@

mkin 0.9.44 (2016-06-29)

Bug fixes

-
  • The test test_FOMC_ill-defined failed on several architectures, so the test is now skipped
+
  • The test test_FOMC_ill-defined failed on several architectures, so the test is now skipped
    • +

mkin 0.9.43 (2016-06-28)

@@ -383,7 +394,8 @@

mkin 0.9.42 (2016-03-25)

Major changes

-
  • Add the argument from_max_mean to mkinfit, for fitting only the decline from the maximum observed value for models with a single observed variable
+
  • Add the argument from_max_mean to mkinfit, for fitting only the decline from the maximum observed value for models with a single observed variable
    • +

Minor changes

  • Add plots to compiled_models vignette

    • @@ -403,18 +415,21 @@

    Bug fixes

    • -print.summary.mkinfit(): Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36
    +print.summary.mkinfit(): Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36 +

mkin 0.9-40 (2015-07-21)

Bug fixes

  • -endpoints(): For DFOP and SFORB models, where optimize() is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as optimize() sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient.
+endpoints(): For DFOP and SFORB models, where optimize() is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as optimize() sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient. +

Internal changes

  • -DESCRIPTION, NAMESPACE, R/*.R: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions.
+DESCRIPTION, NAMESPACE, R/*.R: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions. +

mkin 0.9-39 (2015-06-26)

@@ -426,7 +441,8 @@

Bug fixes

  • -mkinparplot(): Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters.
+mkinparplot(): Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters. +

mkin 0.9-38 (2015-06-24)

@@ -438,7 +454,8 @@

Bug fixes

  • -mkinmod(): When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it.
+mkinmod(): When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it. +

mkin 0.9-36 (2015-06-21)

@@ -451,13 +468,15 @@

Minor changes

-
  • Added a simple showcase vignette with an evaluation of FOCUS example dataset D
+

mkin 0.9-35 (2015-05-15)

Major changes

-
  • Switch from RUnit to testthat for testing
+
  • Switch from RUnit to testthat for testing
    • +

Bug fixes

  • mkinparplot(): Avoid warnings that occurred when not all confidence intervals were available in the summary of the fit

    • @@ -539,13 +558,15 @@

    mkin 0.9-31 (2014-07-14)

    Bug fixes

    -
    • The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in mkinerrmin() used by the summary function.
    +
    • The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in mkinerrmin() used by the summary function.
      • +

mkin 0.9-30 (2014-07-11)

New features

-
  • It is now possible to use formation fractions in combination with turning off the sink in mkinmod().
+
  • It is now possible to use formation fractions in combination with turning off the sink in mkinmod().
    • +

Major changes

  • The original and the transformed parameters now have different names (e.g. k_parent and log_k_parent. They also differ in how many they are when we have formation fractions but no pathway to sink.

    • diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml index 858f6c59..642efcde 100644 --- a/docs/dev/pkgdown.yml +++ b/docs/dev/pkgdown.yml @@ -1,4 +1,4 @@ -pandoc: 2.9.2.1 +pandoc: 2.17.1.1 pkgdown: 2.0.6 pkgdown_sha: ~ articles: @@ -13,7 +13,7 @@ articles: dimethenamid_2018: web_only/dimethenamid_2018.html multistart: web_only/multistart.html saem_benchmarks: web_only/saem_benchmarks.html -last_built: 2022-12-02T13:08Z +last_built: 2022-12-15T13:46Z urls: reference: https://pkgdown.jrwb.de/mkin/reference article: https://pkgdown.jrwb.de/mkin/articles diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png index 8a77fc7f..17a35806 100644 Binary files a/docs/dev/reference/Rplot001.png and b/docs/dev/reference/Rplot001.png differ diff --git a/docs/dev/reference/Rplot002.png b/docs/dev/reference/Rplot002.png index c1621707..27feab09 100644 Binary files a/docs/dev/reference/Rplot002.png and b/docs/dev/reference/Rplot002.png differ diff --git a/docs/dev/reference/illparms.html b/docs/dev/reference/illparms.html index 8fe71568..9c498e1c 100644 --- a/docs/dev/reference/illparms.html +++ b/docs/dev/reference/illparms.html @@ -116,7 +116,14 @@ without parameter transformations is used.

    print(x, ...) # S3 method for saem.mmkin -illparms(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...) +illparms( + object, + conf.level = 0.95, + random = TRUE, + errmod = TRUE, + slopes = TRUE, + ... +) # S3 method for illparms.saem.mmkin print(x, ...) @@ -154,6 +161,12 @@ without parameter transformations is used.

    For hierarchical fits, should error model parameters be tested?

    + +
    slopes
    +

    For hierarchical saem fits using saemix as backend, +should slope parameters in the covariate model(starting with 'beta_') be +tested?

    +

Value

diff --git a/docs/dev/reference/parplot.html b/docs/dev/reference/parplot.html index 9852b694..720c0b2a 100644 --- a/docs/dev/reference/parplot.html +++ b/docs/dev/reference/parplot.html @@ -103,6 +103,7 @@ or by their medians as proposed in the paper by Duchesne et al. (2021).

parplot( object, llmin = -Inf, + llquant = NA, scale = c("best", "median"), lpos = "bottomleft", main = "", @@ -124,8 +125,14 @@ or by their medians as proposed in the paper by Duchesne et al. (2021).

The minimum likelihood of objects to be shown

+
llquant
+

Fractional value for selecting only the fits with higher +likelihoods. Overrides 'llmin'.

+ +
scale
-

By default, scale parameters using the best available fit. +

By default, scale parameters using the best +available fit. If 'median', parameters are scaled using the median parameters from all fits.

diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html index d18cb848..131b168b 100644 --- a/docs/dev/reference/saem.html +++ b/docs/dev/reference/saem.html @@ -432,8 +432,8 @@ using mmkin.

#> saemix version used for fitting: 3.2 #> mkin version used for pre-fitting: 1.2.2 #> R version used for fitting: 4.2.2 -#> Date of fit: Thu Nov 24 08:11:00 2022 -#> Date of summary: Thu Nov 24 08:11:01 2022 +#> Date of fit: Wed Dec 7 16:22:26 2022 +#> Date of summary: Wed Dec 7 16:22:26 2022 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -448,12 +448,12 @@ using mmkin.

#> #> Model predictions using solution type analytical #> -#> Fitted in 8.778 s +#> Fitted in 8.508 s #> Using 300, 100 iterations and 10 chains #> #> Variance model: Constant variance #> -#> Mean of starting values for individual parameters: +#> Starting values for degradation parameters: #> parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 #> 93.8102 -5.3734 -0.9711 -1.8799 -4.2708 #> g_qlogis @@ -462,6 +462,19 @@ using mmkin.

#> Fixed degradation parameter values: #> None #> +#> Starting values for random effects (square root of initial entries in omega): +#> parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis +#> parent_0 4.941 0.000 0.0000 0.000 0.000 0.0000 +#> log_k_A1 0.000 2.551 0.0000 0.000 0.000 0.0000 +#> f_parent_qlogis 0.000 0.000 0.7251 0.000 0.000 0.0000 +#> log_k1 0.000 0.000 0.0000 1.449 0.000 0.0000 +#> log_k2 0.000 0.000 0.0000 0.000 2.228 0.0000 +#> g_qlogis 0.000 0.000 0.0000 0.000 0.000 0.7814 +#> +#> Starting values for error model parameters: +#> a.1 +#> 1 +#> #> Results: #> #> Likelihood computed by importance sampling diff --git a/docs/dev/reference/summary.saem.mmkin.html b/docs/dev/reference/summary.saem.mmkin.html index a4150959..3b5869f1 100644 --- a/docs/dev/reference/summary.saem.mmkin.html +++ b/docs/dev/reference/summary.saem.mmkin.html @@ -102,7 +102,7 @@ endpoints such as formation fractions and DT50 values. Optionally 
# S3 method for saem.mmkin
-summary(object, data = FALSE, verbose = FALSE, distimes = TRUE, ...)
+summary(object, data = FALSE, verbose = FALSE, distimes = TRUE, ...)
 
 # S3 method for summary.saem.mmkin
 print(x, digits = max(3, getOption("digits") - 3), verbose = x$verbose, ...)
@@ -266,36 +266,38 @@ saemix authors for the parts inherited from saemix.

#> SD.g_qlogis 0.37478 0.04490 0.70467 illparms(f_saem_dfop_sfo) #> [1] "sd(parent_0)" "sd(log_k_m1)" -f_saem_dfop_sfo_2 <- update(f_saem_dfop_sfo, covariance.model = diag(c(0, 0, 1, 1, 1, 0))) +f_saem_dfop_sfo_2 <- update(f_saem_dfop_sfo, + no_random_effect = c("parent_0", "log_k_m1")) illparms(f_saem_dfop_sfo_2) intervals(f_saem_dfop_sfo_2) #> Approximate 95% confidence intervals #> #> Fixed effects: #> lower est. upper -#> parent_0 97.57609542 100.73343868 103.89078195 -#> k_m1 0.01549292 0.01714893 0.01898194 -#> f_parent_to_m1 0.20720315 0.28358738 0.37481744 -#> k1 0.06149334 0.08733164 0.12402670 -#> k2 0.01448390 0.01699942 0.01995184 -#> g 0.45084762 0.51075839 0.57036168 +#> parent_0 98.36731429 101.42508066 104.48284703 +#> k_m1 0.01513234 0.01670094 0.01843214 +#> f_parent_to_m1 0.20221431 0.27608850 0.36461630 +#> k1 0.06915073 0.09759718 0.13774560 +#> k2 0.01487068 0.01740389 0.02036863 +#> g 0.37365671 0.48384821 0.59563299 #> #> Random effects: #> lower est. upper -#> sd(f_parent_qlogis) 0.16606767 0.4479731 0.7298784 -#> sd(log_k1) 0.12284609 0.3588446 0.5948430 -#> sd(log_k2) 0.05379723 0.1548780 0.2559588 +#> sd(f_parent_qlogis) 0.16439770 0.4427585 0.7211193 +#> sd(log_k1) 0.08304243 0.3345213 0.5860002 +#> sd(log_k2) 0.03146410 0.1490210 0.2665779 +#> sd(g_qlogis) 0.06216385 0.4023430 0.7425221 #> #> -#> lower est. upper -#> a.1 0.6811490 0.88503409 1.08891921 -#> b.1 0.0676515 0.08336272 0.09907394 -summary(f_saem_dfop_sfo_2, data = TRUE) +#> lower est. upper +#> a.1 0.67696663 0.87777355 1.07858048 +#> b.1 0.06363957 0.07878001 0.09392044 +summary(f_saem_dfop_sfo_2, data = TRUE) #> saemix version used for fitting: 3.2 #> mkin version used for pre-fitting: 1.2.2 #> R version used for fitting: 4.2.2 -#> Date of fit: Thu Nov 24 08:11:52 2022 -#> Date of summary: Thu Nov 24 08:11:52 2022 +#> Date of fit: Thu Dec 15 14:47:14 2022 +#> Date of summary: Thu Dec 15 14:47:14 2022 #> #> Equations: #> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -310,12 +312,12 @@ saemix authors for the parts inherited from saemix.

#> #> Model predictions using solution type analytical #> -#> Fitted in 26.242 s +#> Fitted in 9.623 s #> Using 300, 100 iterations and 10 chains #> #> Variance model: Two-component variance function #> -#> Mean of starting values for individual parameters: +#> Starting values for degradation parameters: #> parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 #> 101.65645 -4.05368 -0.94311 -2.35943 -4.07006 #> g_qlogis @@ -324,237 +326,291 @@ saemix authors for the parts inherited from saemix.

#> Fixed degradation parameter values: #> None #> +#> Starting values for random effects (square root of initial entries in omega): +#> parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 g_qlogis +#> parent_0 6.742 0.0000 0.0000 0.0000 0.0000 0.000 +#> log_k_m1 0.000 0.2236 0.0000 0.0000 0.0000 0.000 +#> f_parent_qlogis 0.000 0.0000 0.5572 0.0000 0.0000 0.000 +#> log_k1 0.000 0.0000 0.0000 0.8031 0.0000 0.000 +#> log_k2 0.000 0.0000 0.0000 0.0000 0.2931 0.000 +#> g_qlogis 0.000 0.0000 0.0000 0.0000 0.0000 0.807 +#> +#> Starting values for error model parameters: +#> a.1 b.1 +#> 1 1 +#> #> Results: #> #> Likelihood computed by importance sampling -#> AIC BIC logLik -#> 809.5 805.2 -393.7 +#> AIC BIC logLik +#> 807 802.3 -391.5 #> #> Optimised parameters: #> est. lower upper -#> parent_0 100.73344 97.57610 103.89078 -#> log_k_m1 -4.06582 -4.16737 -3.96427 -#> f_parent_qlogis -0.92674 -1.34187 -0.51160 -#> log_k1 -2.43804 -2.78883 -2.08726 -#> log_k2 -4.07458 -4.23472 -3.91443 -#> g_qlogis 0.04304 -0.19725 0.28333 -#> a.1 0.88503 0.68115 1.08892 -#> b.1 0.08336 0.06765 0.09907 -#> SD.f_parent_qlogis 0.44797 0.16607 0.72988 -#> SD.log_k1 0.35884 0.12285 0.59484 -#> SD.log_k2 0.15488 0.05380 0.25596 +#> parent_0 101.42508 98.36731 104.48285 +#> log_k_m1 -4.09229 -4.19092 -3.99366 +#> f_parent_qlogis -0.96395 -1.37251 -0.55538 +#> log_k1 -2.32691 -2.67147 -1.98235 +#> log_k2 -4.05106 -4.20836 -3.89376 +#> g_qlogis -0.06463 -0.51656 0.38730 +#> a.1 0.87777 0.67697 1.07858 +#> b.1 0.07878 0.06364 0.09392 +#> SD.f_parent_qlogis 0.44276 0.16440 0.72112 +#> SD.log_k1 0.33452 0.08304 0.58600 +#> SD.log_k2 0.14902 0.03146 0.26658 +#> SD.g_qlogis 0.40234 0.06216 0.74252 #> #> Correlation: #> parnt_0 lg_k_m1 f_prnt_ log_k1 log_k2 -#> log_k_m1 -0.4698 -#> f_parent_qlogis -0.2461 0.2709 -#> log_k1 0.1572 -0.1517 -0.0648 -#> log_k2 -0.0023 0.0835 0.0125 0.1420 -#> g_qlogis 0.2314 -0.2337 -0.0755 -0.2762 -0.4797 +#> log_k_m1 -0.4693 +#> f_parent_qlogis -0.2378 0.2595 +#> log_k1 0.1720 -0.1593 -0.0669 +#> log_k2 0.0179 0.0594 0.0035 0.1995 +#> g_qlogis 0.1073 -0.1060 -0.0322 -0.2299 -0.3168 #> #> Random effects: -#> est. lower upper -#> SD.f_parent_qlogis 0.4480 0.1661 0.7299 -#> SD.log_k1 0.3588 0.1228 0.5948 -#> SD.log_k2 0.1549 0.0538 0.2560 +#> est. lower upper +#> SD.f_parent_qlogis 0.4428 0.16440 0.7211 +#> SD.log_k1 0.3345 0.08304 0.5860 +#> SD.log_k2 0.1490 0.03146 0.2666 +#> SD.g_qlogis 0.4023 0.06216 0.7425 #> #> Variance model: #> est. lower upper -#> a.1 0.88503 0.68115 1.08892 -#> b.1 0.08336 0.06765 0.09907 +#> a.1 0.87777 0.67697 1.07858 +#> b.1 0.07878 0.06364 0.09392 #> #> Backtransformed parameters: -#> est. lower upper -#> parent_0 100.73344 97.57610 103.89078 -#> k_m1 0.01715 0.01549 0.01898 -#> f_parent_to_m1 0.28359 0.20720 0.37482 -#> k1 0.08733 0.06149 0.12403 -#> k2 0.01700 0.01448 0.01995 -#> g 0.51076 0.45085 0.57036 +#> est. lower upper +#> parent_0 101.4251 98.36731 104.48285 +#> k_m1 0.0167 0.01513 0.01843 +#> f_parent_to_m1 0.2761 0.20221 0.36462 +#> k1 0.0976 0.06915 0.13775 +#> k2 0.0174 0.01487 0.02037 +#> g 0.4838 0.37366 0.59563 #> #> Resulting formation fractions: #> ff -#> parent_m1 0.2836 -#> parent_sink 0.7164 +#> parent_m1 0.2761 +#> parent_sink 0.7239 #> #> Estimated disappearance times: #> DT50 DT90 DT50back DT50_k1 DT50_k2 -#> parent 15.94 93.48 28.14 7.937 40.77 -#> m1 40.42 134.27 NA NA NA +#> parent 15.54 94.33 28.4 7.102 39.83 +#> m1 41.50 137.87 NA NA NA #> #> Data: -#> ds name time observed predicted residual std standardized -#> ds 1 parent 0 89.8 1.007e+02 -10.93344 8.4439 -1.29483 -#> ds 1 parent 0 104.1 1.007e+02 3.36656 8.4439 0.39870 -#> ds 1 parent 1 88.7 9.591e+01 -7.20789 8.0440 -0.89606 -#> ds 1 parent 1 95.5 9.591e+01 -0.40789 8.0440 -0.05071 -#> ds 1 parent 3 81.8 8.712e+01 -5.31561 7.3159 -0.72658 -#> ds 1 parent 3 94.5 8.712e+01 7.38439 7.3159 1.00936 -#> ds 1 parent 7 71.5 7.246e+01 -0.95675 6.1047 -0.15672 -#> ds 1 parent 7 70.3 7.246e+01 -2.15675 6.1047 -0.35329 -#> ds 1 parent 14 54.2 5.382e+01 0.38143 4.5729 0.08341 -#> ds 1 parent 14 49.6 5.382e+01 -4.21857 4.5729 -0.92251 -#> ds 1 parent 28 31.5 3.230e+01 -0.80120 2.8344 -0.28267 -#> ds 1 parent 28 28.8 3.230e+01 -3.50120 2.8344 -1.23524 -#> ds 1 parent 60 12.1 1.307e+01 -0.97165 1.4038 -0.69215 -#> ds 1 parent 60 13.6 1.307e+01 0.52835 1.4038 0.37637 -#> ds 1 parent 90 6.2 6.353e+00 -0.15285 1.0314 -0.14820 -#> ds 1 parent 90 8.3 6.353e+00 1.94715 1.0314 1.88790 -#> ds 1 parent 120 2.2 3.175e+00 -0.97462 0.9238 -1.05506 -#> ds 1 parent 120 2.4 3.175e+00 -0.77462 0.9238 -0.83855 -#> ds 1 m1 1 0.3 1.183e+00 -0.88350 0.8905 -0.99212 -#> ds 1 m1 1 0.2 1.183e+00 -0.98350 0.8905 -1.10441 -#> ds 1 m1 3 2.2 3.281e+00 -1.08106 0.9263 -1.16703 -#> ds 1 m1 3 3.0 3.281e+00 -0.28106 0.9263 -0.30341 -#> ds 1 m1 7 6.5 6.564e+00 -0.06353 1.0405 -0.06106 -#> ds 1 m1 7 5.0 6.564e+00 -1.56353 1.0405 -1.50266 -#> ds 1 m1 14 10.2 1.015e+01 0.05147 1.2243 0.04204 -#> ds 1 m1 14 9.5 1.015e+01 -0.64853 1.2243 -0.52970 -#> ds 1 m1 28 12.2 1.265e+01 -0.44824 1.3766 -0.32561 -#> ds 1 m1 28 13.4 1.265e+01 0.75176 1.3766 0.54610 -#> ds 1 m1 60 11.8 1.078e+01 1.02355 1.2611 0.81165 -#> ds 1 m1 60 13.2 1.078e+01 2.42355 1.2611 1.92181 -#> ds 1 m1 90 6.6 7.698e+00 -1.09840 1.0932 -1.00474 -#> ds 1 m1 90 9.3 7.698e+00 1.60160 1.0932 1.46502 -#> ds 1 m1 120 3.5 5.199e+00 -1.69853 0.9854 -1.72363 -#> ds 1 m1 120 5.4 5.199e+00 0.20147 0.9854 0.20445 -#> ds 2 parent 0 118.0 1.007e+02 17.26656 8.4439 2.04485 -#> ds 2 parent 0 99.8 1.007e+02 -0.93344 8.4439 -0.11055 -#> ds 2 parent 1 90.2 9.584e+01 -5.63852 8.0382 -0.70146 -#> ds 2 parent 1 94.6 9.584e+01 -1.23852 8.0382 -0.15408 -#> ds 2 parent 3 96.1 8.706e+01 9.04068 7.3113 1.23654 -#> ds 2 parent 3 78.4 8.706e+01 -8.65932 7.3113 -1.18438 -#> ds 2 parent 7 77.9 7.286e+01 5.04438 6.1376 0.82188 -#> ds 2 parent 7 77.7 7.286e+01 4.84438 6.1376 0.78930 -#> ds 2 parent 14 56.0 5.567e+01 0.33336 4.7242 0.07057 -#> ds 2 parent 14 54.7 5.567e+01 -0.96664 4.7242 -0.20462 -#> ds 2 parent 28 36.6 3.705e+01 -0.44800 3.2127 -0.13944 -#> ds 2 parent 28 36.8 3.705e+01 -0.24800 3.2127 -0.07719 -#> ds 2 parent 60 22.1 2.008e+01 2.01984 1.8935 1.06672 -#> ds 2 parent 60 24.7 2.008e+01 4.61984 1.8935 2.43984 -#> ds 2 parent 90 12.4 1.253e+01 -0.12814 1.3689 -0.09360 -#> ds 2 parent 90 10.8 1.253e+01 -1.72814 1.3689 -1.26238 -#> ds 2 parent 120 6.8 7.916e+00 -1.11595 1.1040 -1.01085 -#> ds 2 parent 120 7.9 7.916e+00 -0.01595 1.1040 -0.01445 -#> ds 2 m1 1 1.3 1.317e+00 -0.01669 0.8918 -0.01871 -#> ds 2 m1 3 3.7 3.613e+00 0.08699 0.9349 0.09305 -#> ds 2 m1 3 4.7 3.613e+00 1.08699 0.9349 1.16270 -#> ds 2 m1 7 8.1 7.092e+00 1.00781 1.0643 0.94688 -#> ds 2 m1 7 7.9 7.092e+00 0.80781 1.0643 0.75897 -#> ds 2 m1 14 10.1 1.066e+01 -0.56458 1.2545 -0.45006 -#> ds 2 m1 14 10.3 1.066e+01 -0.36458 1.2545 -0.29063 -#> ds 2 m1 28 10.7 1.281e+01 -2.11106 1.3870 -1.52201 -#> ds 2 m1 28 12.2 1.281e+01 -0.61106 1.3870 -0.44055 -#> ds 2 m1 60 10.7 1.078e+01 -0.08464 1.2616 -0.06709 -#> ds 2 m1 60 12.5 1.078e+01 1.71536 1.2616 1.35970 -#> ds 2 m1 90 9.1 8.013e+00 1.08684 1.1088 0.98016 -#> ds 2 m1 90 7.4 8.013e+00 -0.61316 1.1088 -0.55298 -#> ds 2 m1 120 6.1 5.749e+00 0.35063 1.0065 0.34838 -#> ds 2 m1 120 4.5 5.749e+00 -1.24937 1.0065 -1.24133 -#> ds 3 parent 0 106.2 1.007e+02 5.46656 8.4439 0.64740 -#> ds 3 parent 0 106.9 1.007e+02 6.16656 8.4439 0.73030 -#> ds 3 parent 1 107.4 9.369e+01 13.70530 7.8606 1.74354 -#> ds 3 parent 1 96.1 9.369e+01 2.40530 7.8606 0.30599 -#> ds 3 parent 3 79.4 8.185e+01 -2.45363 6.8807 -0.35660 -#> ds 3 parent 3 82.6 8.185e+01 0.74637 6.8807 0.10847 -#> ds 3 parent 7 63.9 6.487e+01 -0.97153 5.4798 -0.17729 -#> ds 3 parent 7 62.4 6.487e+01 -2.47153 5.4798 -0.45103 -#> ds 3 parent 14 51.0 4.791e+01 3.09024 4.0908 0.75542 -#> ds 3 parent 14 47.1 4.791e+01 -0.80976 4.0908 -0.19795 -#> ds 3 parent 28 36.1 3.313e+01 2.97112 2.9001 1.02450 -#> ds 3 parent 28 36.6 3.313e+01 3.47112 2.9001 1.19691 -#> ds 3 parent 60 20.1 1.927e+01 0.83265 1.8339 0.45404 -#> ds 3 parent 60 19.8 1.927e+01 0.53265 1.8339 0.29045 -#> ds 3 parent 90 11.3 1.203e+01 -0.72783 1.3374 -0.54421 -#> ds 3 parent 90 10.7 1.203e+01 -1.32783 1.3374 -0.99284 -#> ds 3 parent 120 8.2 7.516e+00 0.68382 1.0844 0.63061 -#> ds 3 parent 120 7.3 7.516e+00 -0.21618 1.0844 -0.19936 -#> ds 3 m1 0 0.8 -9.948e-14 0.80000 0.8850 0.90392 -#> ds 3 m1 1 1.8 1.682e+00 0.11759 0.8961 0.13123 -#> ds 3 m1 1 2.3 1.682e+00 0.61759 0.8961 0.68921 -#> ds 3 m1 3 4.2 4.431e+00 -0.23052 0.9590 -0.24037 -#> ds 3 m1 3 4.1 4.431e+00 -0.33052 0.9590 -0.34465 -#> ds 3 m1 7 6.8 8.084e+00 -1.28422 1.1124 -1.15445 -#> ds 3 m1 7 10.1 8.084e+00 2.01578 1.1124 1.81208 -#> ds 3 m1 14 11.4 1.100e+01 0.40274 1.2743 0.31606 -#> ds 3 m1 14 12.8 1.100e+01 1.80274 1.2743 1.41474 -#> ds 3 m1 28 11.5 1.176e+01 -0.25977 1.3207 -0.19669 -#> ds 3 m1 28 10.6 1.176e+01 -1.15977 1.3207 -0.87813 -#> ds 3 m1 60 7.5 9.277e+00 -1.77696 1.1753 -1.51190 -#> ds 3 m1 60 8.6 9.277e+00 -0.67696 1.1753 -0.57598 -#> ds 3 m1 90 7.3 6.883e+00 0.41708 1.0548 0.39542 -#> ds 3 m1 90 8.1 6.883e+00 1.21708 1.0548 1.15389 -#> ds 3 m1 120 5.3 4.948e+00 0.35179 0.9764 0.36028 -#> ds 3 m1 120 3.8 4.948e+00 -1.14821 0.9764 -1.17591 -#> ds 4 parent 0 104.7 1.007e+02 3.96656 8.4439 0.46975 -#> ds 4 parent 0 88.3 1.007e+02 -12.43344 8.4439 -1.47247 -#> ds 4 parent 1 94.2 9.738e+01 -3.18358 8.1663 -0.38985 -#> ds 4 parent 1 94.6 9.738e+01 -2.78358 8.1663 -0.34086 -#> ds 4 parent 3 78.1 9.110e+01 -12.99595 7.6454 -1.69984 -#> ds 4 parent 3 96.5 9.110e+01 5.40405 7.6454 0.70684 -#> ds 4 parent 7 76.2 8.000e+01 -3.79797 6.7273 -0.56456 -#> ds 4 parent 7 77.8 8.000e+01 -2.19797 6.7273 -0.32672 -#> ds 4 parent 14 70.8 6.446e+01 6.34396 5.4456 1.16496 -#> ds 4 parent 14 67.3 6.446e+01 2.84396 5.4456 0.52225 -#> ds 4 parent 28 43.1 4.359e+01 -0.48960 3.7400 -0.13091 -#> ds 4 parent 28 45.1 4.359e+01 1.51040 3.7400 0.40385 -#> ds 4 parent 60 21.3 2.095e+01 0.35282 1.9577 0.18022 -#> ds 4 parent 60 23.5 2.095e+01 2.55282 1.9577 1.30400 -#> ds 4 parent 90 11.8 1.188e+01 -0.07874 1.3281 -0.05929 -#> ds 4 parent 90 12.1 1.188e+01 0.22126 1.3281 0.16660 -#> ds 4 parent 120 7.0 7.072e+00 -0.07245 1.0634 -0.06813 -#> ds 4 parent 120 6.2 7.072e+00 -0.87245 1.0634 -0.82041 -#> ds 4 m1 0 1.6 5.684e-14 1.60000 0.8850 1.80784 -#> ds 4 m1 1 0.9 6.960e-01 0.20399 0.8869 0.23000 -#> ds 4 m1 3 3.7 1.968e+00 1.73240 0.9001 1.92466 -#> ds 4 m1 3 2.0 1.968e+00 0.03240 0.9001 0.03599 -#> ds 4 m1 7 3.6 4.083e+00 -0.48287 0.9482 -0.50924 -#> ds 4 m1 7 3.8 4.083e+00 -0.28287 0.9482 -0.29832 -#> ds 4 m1 14 7.1 6.682e+00 0.41836 1.0457 0.40007 -#> ds 4 m1 14 6.6 6.682e+00 -0.08164 1.0457 -0.07807 -#> ds 4 m1 28 9.5 9.103e+00 0.39733 1.1658 0.34082 -#> ds 4 m1 28 9.3 9.103e+00 0.19733 1.1658 0.16926 -#> ds 4 m1 60 8.3 8.750e+00 -0.44979 1.1469 -0.39218 -#> ds 4 m1 60 9.0 8.750e+00 0.25021 1.1469 0.21817 -#> ds 4 m1 90 6.6 6.673e+00 -0.07285 1.0453 -0.06969 -#> ds 4 m1 90 7.7 6.673e+00 1.02715 1.0453 0.98261 -#> ds 4 m1 120 3.7 4.757e+00 -1.05747 0.9698 -1.09036 -#> ds 4 m1 120 3.5 4.757e+00 -1.25747 0.9698 -1.29658 -#> ds 5 parent 0 110.4 1.007e+02 9.66656 8.4439 1.14480 -#> ds 5 parent 0 112.1 1.007e+02 11.36656 8.4439 1.34612 -#> ds 5 parent 1 93.5 9.395e+01 -0.45394 7.8821 -0.05759 -#> ds 5 parent 1 91.0 9.395e+01 -2.95394 7.8821 -0.37477 -#> ds 5 parent 3 71.0 8.245e+01 -11.44783 6.9298 -1.65197 -#> ds 5 parent 3 89.7 8.245e+01 7.25217 6.9298 1.04652 -#> ds 5 parent 7 60.4 6.567e+01 -5.27002 5.5455 -0.95032 -#> ds 5 parent 7 59.1 6.567e+01 -6.57002 5.5455 -1.18475 -#> ds 5 parent 14 56.5 4.847e+01 8.03029 4.1364 1.94139 -#> ds 5 parent 14 47.0 4.847e+01 -1.46971 4.1364 -0.35532 -#> ds 5 parent 28 30.2 3.309e+01 -2.89206 2.8971 -0.99825 -#> ds 5 parent 28 23.9 3.309e+01 -9.19206 2.8971 -3.17281 -#> ds 5 parent 60 17.0 1.891e+01 -1.90623 1.8076 -1.05458 -#> ds 5 parent 60 18.7 1.891e+01 -0.20623 1.8076 -0.11409 -#> ds 5 parent 90 11.3 1.168e+01 -0.38263 1.3160 -0.29076 -#> ds 5 parent 90 11.9 1.168e+01 0.21737 1.3160 0.16518 -#> ds 5 parent 120 9.0 7.230e+00 1.77031 1.0708 1.65333 -#> ds 5 parent 120 8.1 7.230e+00 0.87031 1.0708 0.81280 -#> ds 5 m1 0 0.7 -5.116e-13 0.70000 0.8850 0.79093 -#> ds 5 m1 1 3.0 3.244e+00 -0.24430 0.9254 -0.26398 -#> ds 5 m1 1 2.6 3.244e+00 -0.64430 0.9254 -0.69621 -#> ds 5 m1 3 5.1 8.592e+00 -3.49175 1.1385 -3.06686 -#> ds 5 m1 3 7.5 8.592e+00 -1.09175 1.1385 -0.95890 -#> ds 5 m1 7 16.5 1.583e+01 0.66887 1.5890 0.42093 -#> ds 5 m1 7 19.0 1.583e+01 3.16887 1.5890 1.99424 -#> ds 5 m1 14 22.9 2.181e+01 1.08658 2.0224 0.53728 -#> ds 5 m1 14 23.2 2.181e+01 1.38658 2.0224 0.68562 -#> ds 5 m1 28 22.2 2.364e+01 -1.43659 2.1600 -0.66508 -#> ds 5 m1 28 24.4 2.364e+01 0.76341 2.1600 0.35342 -#> ds 5 m1 60 15.5 1.873e+01 -3.23377 1.7950 -1.80150 -#> ds 5 m1 60 19.8 1.873e+01 1.06623 1.7950 0.59398 -#> ds 5 m1 90 14.9 1.387e+01 1.03117 1.4560 0.70822 -#> ds 5 m1 90 14.2 1.387e+01 0.33117 1.4560 0.22745 -#> ds 5 m1 120 10.9 9.937e+00 0.96270 1.2122 0.79415 -#> ds 5 m1 120 10.4 9.937e+00 0.46270 1.2122 0.38169 +#> ds name time observed predicted residual std standardized +#> ds 1 parent 0 89.8 1.014e+02 -11.62508 8.0383 -1.44620 +#> ds 1 parent 0 104.1 1.014e+02 2.67492 8.0383 0.33277 +#> ds 1 parent 1 88.7 9.650e+01 -7.80311 7.6530 -1.01961 +#> ds 1 parent 1 95.5 9.650e+01 -1.00311 7.6530 -0.13107 +#> ds 1 parent 3 81.8 8.753e+01 -5.72638 6.9510 -0.82382 +#> ds 1 parent 3 94.5 8.753e+01 6.97362 6.9510 1.00326 +#> ds 1 parent 7 71.5 7.254e+01 -1.04133 5.7818 -0.18010 +#> ds 1 parent 7 70.3 7.254e+01 -2.24133 5.7818 -0.38765 +#> ds 1 parent 14 54.2 5.349e+01 0.71029 4.3044 0.16502 +#> ds 1 parent 14 49.6 5.349e+01 -3.88971 4.3044 -0.90366 +#> ds 1 parent 28 31.5 3.167e+01 -0.16616 2.6446 -0.06283 +#> ds 1 parent 28 28.8 3.167e+01 -2.86616 2.6446 -1.08379 +#> ds 1 parent 60 12.1 1.279e+01 -0.69287 1.3365 -0.51843 +#> ds 1 parent 60 13.6 1.279e+01 0.80713 1.3365 0.60392 +#> ds 1 parent 90 6.2 6.397e+00 -0.19718 1.0122 -0.19481 +#> ds 1 parent 90 8.3 6.397e+00 1.90282 1.0122 1.87996 +#> ds 1 parent 120 2.2 3.323e+00 -1.12320 0.9160 -1.22623 +#> ds 1 parent 120 2.4 3.323e+00 -0.92320 0.9160 -1.00788 +#> ds 1 m1 1 0.3 1.179e+00 -0.87919 0.8827 -0.99605 +#> ds 1 m1 1 0.2 1.179e+00 -0.97919 0.8827 -1.10935 +#> ds 1 m1 3 2.2 3.273e+00 -1.07272 0.9149 -1.17256 +#> ds 1 m1 3 3.0 3.273e+00 -0.27272 0.9149 -0.29811 +#> ds 1 m1 7 6.5 6.559e+00 -0.05872 1.0186 -0.05765 +#> ds 1 m1 7 5.0 6.559e+00 -1.55872 1.0186 -1.53032 +#> ds 1 m1 14 10.2 1.016e+01 0.03787 1.1880 0.03188 +#> ds 1 m1 14 9.5 1.016e+01 -0.66213 1.1880 -0.55734 +#> ds 1 m1 28 12.2 1.268e+01 -0.47913 1.3297 -0.36032 +#> ds 1 m1 28 13.4 1.268e+01 0.72087 1.3297 0.54211 +#> ds 1 m1 60 11.8 1.078e+01 1.02493 1.2211 0.83936 +#> ds 1 m1 60 13.2 1.078e+01 2.42493 1.2211 1.98588 +#> ds 1 m1 90 6.6 7.705e+00 -1.10464 1.0672 -1.03509 +#> ds 1 m1 90 9.3 7.705e+00 1.59536 1.0672 1.49491 +#> ds 1 m1 120 3.5 5.236e+00 -1.73617 0.9699 -1.79010 +#> ds 1 m1 120 5.4 5.236e+00 0.16383 0.9699 0.16892 +#> ds 2 parent 0 118.0 1.014e+02 16.57492 8.0383 2.06198 +#> ds 2 parent 0 99.8 1.014e+02 -1.62508 8.0383 -0.20217 +#> ds 2 parent 1 90.2 9.599e+01 -5.79045 7.6129 -0.76061 +#> ds 2 parent 1 94.6 9.599e+01 -1.39045 7.6129 -0.18264 +#> ds 2 parent 3 96.1 8.652e+01 9.57931 6.8724 1.39388 +#> ds 2 parent 3 78.4 8.652e+01 -8.12069 6.8724 -1.18164 +#> ds 2 parent 7 77.9 7.197e+01 5.93429 5.7370 1.03439 +#> ds 2 parent 7 77.7 7.197e+01 5.73429 5.7370 0.99953 +#> ds 2 parent 14 56.0 5.555e+01 0.44657 4.4637 0.10005 +#> ds 2 parent 14 54.7 5.555e+01 -0.85343 4.4637 -0.19120 +#> ds 2 parent 28 36.6 3.853e+01 -1.93170 3.1599 -0.61132 +#> ds 2 parent 28 36.8 3.853e+01 -1.73170 3.1599 -0.54803 +#> ds 2 parent 60 22.1 2.110e+01 1.00360 1.8795 0.53396 +#> ds 2 parent 60 24.7 2.110e+01 3.60360 1.8795 1.91728 +#> ds 2 parent 90 12.4 1.250e+01 -0.09712 1.3190 -0.07363 +#> ds 2 parent 90 10.8 1.250e+01 -1.69712 1.3190 -1.28667 +#> ds 2 parent 120 6.8 7.419e+00 -0.61913 1.0546 -0.58709 +#> ds 2 parent 120 7.9 7.419e+00 0.48087 1.0546 0.45599 +#> ds 2 m1 1 1.3 1.422e+00 -0.12194 0.8849 -0.13781 +#> ds 2 m1 3 3.7 3.831e+00 -0.13149 0.9282 -0.14166 +#> ds 2 m1 3 4.7 3.831e+00 0.86851 0.9282 0.93567 +#> ds 2 m1 7 8.1 7.292e+00 0.80812 1.0490 0.77034 +#> ds 2 m1 7 7.9 7.292e+00 0.60812 1.0490 0.57969 +#> ds 2 m1 14 10.1 1.055e+01 -0.45332 1.2090 -0.37495 +#> ds 2 m1 14 10.3 1.055e+01 -0.25332 1.2090 -0.20953 +#> ds 2 m1 28 10.7 1.230e+01 -1.59960 1.3074 -1.22347 +#> ds 2 m1 28 12.2 1.230e+01 -0.09960 1.3074 -0.07618 +#> ds 2 m1 60 10.7 1.065e+01 0.05342 1.2141 0.04400 +#> ds 2 m1 60 12.5 1.065e+01 1.85342 1.2141 1.52661 +#> ds 2 m1 90 9.1 8.196e+00 0.90368 1.0897 0.82930 +#> ds 2 m1 90 7.4 8.196e+00 -0.79632 1.0897 -0.73078 +#> ds 2 m1 120 6.1 5.997e+00 0.10252 0.9969 0.10284 +#> ds 2 m1 120 4.5 5.997e+00 -1.49748 0.9969 -1.50220 +#> ds 3 parent 0 106.2 1.014e+02 4.77492 8.0383 0.59402 +#> ds 3 parent 0 106.9 1.014e+02 5.47492 8.0383 0.68110 +#> ds 3 parent 1 107.4 9.390e+01 13.49935 7.4494 1.81214 +#> ds 3 parent 1 96.1 9.390e+01 2.19935 7.4494 0.29524 +#> ds 3 parent 3 79.4 8.152e+01 -2.12307 6.4821 -0.32753 +#> ds 3 parent 3 82.6 8.152e+01 1.07693 6.4821 0.16614 +#> ds 3 parent 7 63.9 6.446e+01 -0.55834 5.1533 -0.10834 +#> ds 3 parent 7 62.4 6.446e+01 -2.05834 5.1533 -0.39942 +#> ds 3 parent 14 51.0 4.826e+01 2.74073 3.9019 0.70241 +#> ds 3 parent 14 47.1 4.826e+01 -1.15927 3.9019 -0.29711 +#> ds 3 parent 28 36.1 3.424e+01 1.86399 2.8364 0.65718 +#> ds 3 parent 28 36.6 3.424e+01 2.36399 2.8364 0.83346 +#> ds 3 parent 60 20.1 1.968e+01 0.42172 1.7815 0.23672 +#> ds 3 parent 60 19.8 1.968e+01 0.12172 1.7815 0.06833 +#> ds 3 parent 90 11.3 1.195e+01 -0.64633 1.2869 -0.50222 +#> ds 3 parent 90 10.7 1.195e+01 -1.24633 1.2869 -0.96844 +#> ds 3 parent 120 8.2 7.255e+00 0.94532 1.0474 0.90251 +#> ds 3 parent 120 7.3 7.255e+00 0.04532 1.0474 0.04327 +#> ds 3 m1 0 0.8 2.956e-11 0.80000 0.8778 0.91140 +#> ds 3 m1 1 1.8 1.758e+00 0.04187 0.8886 0.04712 +#> ds 3 m1 1 2.3 1.758e+00 0.54187 0.8886 0.60978 +#> ds 3 m1 3 4.2 4.567e+00 -0.36697 0.9486 -0.38683 +#> ds 3 m1 3 4.1 4.567e+00 -0.46697 0.9486 -0.49224 +#> ds 3 m1 7 6.8 8.151e+00 -1.35124 1.0876 -1.24242 +#> ds 3 m1 7 10.1 8.151e+00 1.94876 1.0876 1.79182 +#> ds 3 m1 14 11.4 1.083e+01 0.57098 1.2240 0.46647 +#> ds 3 m1 14 12.8 1.083e+01 1.97098 1.2240 1.61022 +#> ds 3 m1 28 11.5 1.147e+01 0.03175 1.2597 0.02520 +#> ds 3 m1 28 10.6 1.147e+01 -0.86825 1.2597 -0.68928 +#> ds 3 m1 60 7.5 9.298e+00 -1.79834 1.1433 -1.57298 +#> ds 3 m1 60 8.6 9.298e+00 -0.69834 1.1433 -0.61083 +#> ds 3 m1 90 7.3 7.038e+00 0.26249 1.0382 0.25283 +#> ds 3 m1 90 8.1 7.038e+00 1.06249 1.0382 1.02340 +#> ds 3 m1 120 5.3 5.116e+00 0.18417 0.9659 0.19068 +#> ds 3 m1 120 3.8 5.116e+00 -1.31583 0.9659 -1.36232 +#> ds 4 parent 0 104.7 1.014e+02 3.27492 8.0383 0.40741 +#> ds 4 parent 0 88.3 1.014e+02 -13.12508 8.0383 -1.63281 +#> ds 4 parent 1 94.2 9.781e+01 -3.61183 7.7555 -0.46572 +#> ds 4 parent 1 94.6 9.781e+01 -3.21183 7.7555 -0.41414 +#> ds 4 parent 3 78.1 9.110e+01 -13.00467 7.2307 -1.79853 +#> ds 4 parent 3 96.5 9.110e+01 5.39533 7.2307 0.74617 +#> ds 4 parent 7 76.2 7.951e+01 -3.30511 6.3246 -0.52258 +#> ds 4 parent 7 77.8 7.951e+01 -1.70511 6.3246 -0.26960 +#> ds 4 parent 14 70.8 6.376e+01 7.03783 5.0993 1.38016 +#> ds 4 parent 14 67.3 6.376e+01 3.53783 5.0993 0.69379 +#> ds 4 parent 28 43.1 4.340e+01 -0.30456 3.5303 -0.08627 +#> ds 4 parent 28 45.1 4.340e+01 1.69544 3.5303 0.48026 +#> ds 4 parent 60 21.3 2.142e+01 -0.12077 1.9022 -0.06349 +#> ds 4 parent 60 23.5 2.142e+01 2.07923 1.9022 1.09308 +#> ds 4 parent 90 11.8 1.207e+01 -0.26813 1.2940 -0.20721 +#> ds 4 parent 90 12.1 1.207e+01 0.03187 1.2940 0.02463 +#> ds 4 parent 120 7.0 6.954e+00 0.04554 1.0347 0.04402 +#> ds 4 parent 120 6.2 6.954e+00 -0.75446 1.0347 -0.72914 +#> ds 4 m1 0 1.6 1.990e-13 1.60000 0.8778 1.82279 +#> ds 4 m1 1 0.9 7.305e-01 0.16949 0.8797 0.19267 +#> ds 4 m1 3 3.7 2.051e+00 1.64896 0.8925 1.84753 +#> ds 4 m1 3 2.0 2.051e+00 -0.05104 0.8925 -0.05719 +#> ds 4 m1 7 3.6 4.204e+00 -0.60375 0.9382 -0.64354 +#> ds 4 m1 7 3.8 4.204e+00 -0.40375 0.9382 -0.43036 +#> ds 4 m1 14 7.1 6.760e+00 0.34021 1.0267 0.33137 +#> ds 4 m1 14 6.6 6.760e+00 -0.15979 1.0267 -0.15563 +#> ds 4 m1 28 9.5 9.011e+00 0.48856 1.1289 0.43277 +#> ds 4 m1 28 9.3 9.011e+00 0.28856 1.1289 0.25561 +#> ds 4 m1 60 8.3 8.611e+00 -0.31077 1.1093 -0.28014 +#> ds 4 m1 60 9.0 8.611e+00 0.38923 1.1093 0.35086 +#> ds 4 m1 90 6.6 6.678e+00 -0.07753 1.0233 -0.07576 +#> ds 4 m1 90 7.7 6.678e+00 1.02247 1.0233 0.99915 +#> ds 4 m1 120 3.7 4.847e+00 -1.14679 0.9572 -1.19804 +#> ds 4 m1 120 3.5 4.847e+00 -1.34679 0.9572 -1.40698 +#> ds 5 parent 0 110.4 1.014e+02 8.97492 8.0383 1.11651 +#> ds 5 parent 0 112.1 1.014e+02 10.67492 8.0383 1.32800 +#> ds 5 parent 1 93.5 9.466e+01 -1.16118 7.5089 -0.15464 +#> ds 5 parent 1 91.0 9.466e+01 -3.66118 7.5089 -0.48758 +#> ds 5 parent 3 71.0 8.302e+01 -12.01844 6.5988 -1.82130 +#> ds 5 parent 3 89.7 8.302e+01 6.68156 6.5988 1.01254 +#> ds 5 parent 7 60.4 6.563e+01 -5.22574 5.2440 -0.99652 +#> ds 5 parent 7 59.1 6.563e+01 -6.52574 5.2440 -1.24442 +#> ds 5 parent 14 56.5 4.727e+01 9.22621 3.8263 2.41128 +#> ds 5 parent 14 47.0 4.727e+01 -0.27379 3.8263 -0.07156 +#> ds 5 parent 28 30.2 3.103e+01 -0.83405 2.5977 -0.32108 +#> ds 5 parent 28 23.9 3.103e+01 -7.13405 2.5977 -2.74634 +#> ds 5 parent 60 17.0 1.800e+01 -0.99696 1.6675 -0.59787 +#> ds 5 parent 60 18.7 1.800e+01 0.70304 1.6675 0.42161 +#> ds 5 parent 90 11.3 1.167e+01 -0.36809 1.2710 -0.28961 +#> ds 5 parent 90 11.9 1.167e+01 0.23191 1.2710 0.18246 +#> ds 5 parent 120 9.0 7.595e+00 1.40496 1.0623 1.32256 +#> ds 5 parent 120 8.1 7.595e+00 0.50496 1.0623 0.47535 +#> ds 5 m1 0 0.7 0.000e+00 0.70000 0.8778 0.79747 +#> ds 5 m1 1 3.0 3.158e+00 -0.15799 0.9123 -0.17317 +#> ds 5 m1 1 2.6 3.158e+00 -0.55799 0.9123 -0.61160 +#> ds 5 m1 3 5.1 8.443e+00 -3.34286 1.1013 -3.03535 +#> ds 5 m1 3 7.5 8.443e+00 -0.94286 1.1013 -0.85613 +#> ds 5 m1 7 16.5 1.580e+01 0.69781 1.5232 0.45811 +#> ds 5 m1 7 19.0 1.580e+01 3.19781 1.5232 2.09935 +#> ds 5 m1 14 22.9 2.216e+01 0.73604 1.9543 0.37663 +#> ds 5 m1 14 23.2 2.216e+01 1.03604 1.9543 0.53014 +#> ds 5 m1 28 22.2 2.423e+01 -2.03128 2.1011 -0.96678 +#> ds 5 m1 28 24.4 2.423e+01 0.16872 2.1011 0.08030 +#> ds 5 m1 60 15.5 1.876e+01 -3.25610 1.7187 -1.89455 +#> ds 5 m1 60 19.8 1.876e+01 1.04390 1.7187 0.60739 +#> ds 5 m1 90 14.9 1.366e+01 1.23585 1.3890 0.88976 +#> ds 5 m1 90 14.2 1.366e+01 0.53585 1.3890 0.38579 +#> ds 5 m1 120 10.9 9.761e+00 1.13911 1.1670 0.97613 +#> ds 5 m1 120 10.4 9.761e+00 0.63911 1.1670 0.54767 +# Add a correlation between random effects of g and k2 +cov_model_3 <- f_saem_dfop_sfo_2$so@model@covariance.model +cov_model_3["log_k2", "g_qlogis"] <- 1 +cov_model_3["g_qlogis", "log_k2"] <- 1 +f_saem_dfop_sfo_3 <- update(f_saem_dfop_sfo, + covariance.model = cov_model_3) +intervals(f_saem_dfop_sfo_3) +#> Approximate 95% confidence intervals +#> +#> Fixed effects: +#> lower est. upper +#> parent_0 98.39888363 101.48951337 104.58014311 +#> k_m1 0.01508704 0.01665986 0.01839665 +#> f_parent_to_m1 0.20141557 0.27540583 0.36418131 +#> k1 0.07708759 0.10430866 0.14114200 +#> k2 0.01476621 0.01786384 0.02161129 +#> g 0.33679867 0.45083525 0.57028162 +#> +#> Random effects: +#> lower est. upper +#> sd(f_parent_qlogis) 0.38085375 0.4441841 0.5075145 +#> sd(log_k1) 0.04774819 0.2660384 0.4843286 +#> sd(log_k2) -0.63842736 0.1977024 1.0338321 +#> sd(g_qlogis) 0.22711289 0.4502227 0.6733326 +#> corr(log_k2,g_qlogis) -0.83271473 -0.6176939 -0.4026730 +#> +#> +#> lower est. upper +#> a.1 0.67347568 0.87437392 1.07527216 +#> b.1 0.06393032 0.07912417 0.09431802 +# The correlation does not improve the fit judged by AIC and BIC, although +# the likelihood is higher with the additional parameter +anova(f_saem_dfop_sfo, f_saem_dfop_sfo_2, f_saem_dfop_sfo_3) +#> Data: 171 observations of 2 variable(s) grouped in 5 datasets +#> +#> npar AIC BIC Lik +#> f_saem_dfop_sfo_2 12 806.96 802.27 -391.48 +#> f_saem_dfop_sfo_3 13 807.99 802.91 -391.00 +#> f_saem_dfop_sfo 14 810.83 805.36 -391.42 # }
diff --git a/log/test.log b/log/test.log index 89265100..dc1b6c74 100644 --- a/log/test.log +++ b/log/test.log @@ -1,11 +1,11 @@ ℹ Testing mkin ✔ | F W S OK | Context ✔ | 5 | AIC calculation -✔ | 5 | Analytical solutions for coupled models [1.5s] +✔ | 5 | Analytical solutions for coupled models [1.6s] ✔ | 5 | Calculation of Akaike weights ✔ | 3 | Export dataset for reading into CAKE ✔ | 12 | Confidence intervals and p-values [0.4s] -✔ | 1 12 | Dimethenamid data from 2018 [12.3s] +✔ | 1 12 | Dimethenamid data from 2018 [12.4s] ──────────────────────────────────────────────────────────────────────────────── Skip ('test_dmta.R:98'): Different backends get consistent results for SFO-SFO3+, dimethenamid data Reason: Fitting this ODE model with saemix takes about 15 minutes on my system @@ -16,23 +16,23 @@ Reason: Fitting this ODE model with saemix takes about 15 minutes on my system ✔ | 14 | Results for FOCUS D established in expertise for UBA (Ranke 2014) [0.4s] ✔ | 4 | Test fitting the decline of metabolites from their maximum [0.2s] ✔ | 1 | Fitting the logistic model [0.1s] -✔ | 10 | Batch fitting and diagnosing hierarchical kinetic models [18.2s] -✔ | 1 11 | Nonlinear mixed-effects models [5.8s] +✔ | 10 | Batch fitting and diagnosing hierarchical kinetic models [19.1s] +✔ | 1 11 | Nonlinear mixed-effects models [5.9s] ──────────────────────────────────────────────────────────────────────────────── Skip ('test_mixed.R:78'): saemix results are reproducible for biphasic fits Reason: Fitting with saemix takes around 10 minutes when using deSolve ──────────────────────────────────────────────────────────────────────────────── ✔ | 3 | Test dataset classes mkinds and mkindsg ✔ | 10 | Special cases of mkinfit calls [0.4s] -✔ | 3 | mkinfit features [0.4s] +✔ | 3 | mkinfit features [0.5s] ✔ | 8 | mkinmod model generation and printing ✔ | 3 | Model predictions with mkinpredict [0.1s] -✔ | 12 | Multistart method for saem.mmkin models [20.6s] -✔ | 16 | Evaluations according to 2015 NAFTA guidance [1.4s] +✔ | 12 | Multistart method for saem.mmkin models [21.6s] +✔ | 16 | Evaluations according to 2015 NAFTA guidance [1.5s] ✔ | 9 | Nonlinear mixed-effects models with nlme [3.7s] -✔ | 15 | Plotting [4.7s] +✔ | 15 | Plotting [4.6s] ✔ | 4 | Residuals extracted from mkinfit models -✔ | 1 36 | saemix parent models [30.6s] +✔ | 1 36 | saemix parent models [30.9s] ──────────────────────────────────────────────────────────────────────────────── Skip ('test_saemix_parent.R:143'): We can also use mkin solution methods for saem Reason: This still takes almost 2.5 minutes although we do not solve ODEs @@ -47,7 +47,7 @@ Reason: This still takes almost 2.5 minutes although we do not solve ODEs ✔ | 4 | Calculation of maximum time weighted average concentrations (TWAs) [0.7s] ══ Results ═════════════════════════════════════════════════════════════════════ -Duration: 111.2 s +Duration: 113.6 s ── Skipped tests ────────────────────────────────────────────────────────────── • Fitting this ODE model with saemix takes about 15 minutes on my system (1) diff --git a/man/summary.saem.mmkin.Rd b/man/summary.saem.mmkin.Rd index fb099899..0845d4d2 100644 --- a/man/summary.saem.mmkin.Rd +++ b/man/summary.saem.mmkin.Rd @@ -92,10 +92,21 @@ f_mmkin_dfop_sfo <- mmkin(list(dfop_sfo), ds_syn_dfop_sfo, f_saem_dfop_sfo <- saem(f_mmkin_dfop_sfo) print(f_saem_dfop_sfo) illparms(f_saem_dfop_sfo) -f_saem_dfop_sfo_2 <- update(f_saem_dfop_sfo, covariance.model = diag(c(0, 0, 1, 1, 1, 0))) +f_saem_dfop_sfo_2 <- update(f_saem_dfop_sfo, + no_random_effect = c("parent_0", "log_k_m1")) illparms(f_saem_dfop_sfo_2) intervals(f_saem_dfop_sfo_2) summary(f_saem_dfop_sfo_2, data = TRUE) +# Add a correlation between random effects of g and k2 +cov_model_3 <- f_saem_dfop_sfo_2$so@model@covariance.model +cov_model_3["log_k2", "g_qlogis"] <- 1 +cov_model_3["g_qlogis", "log_k2"] <- 1 +f_saem_dfop_sfo_3 <- update(f_saem_dfop_sfo, + covariance.model = cov_model_3) +intervals(f_saem_dfop_sfo_3) +# The correlation does not improve the fit judged by AIC and BIC, although +# the likelihood is higher with the additional parameter +anova(f_saem_dfop_sfo, f_saem_dfop_sfo_2, f_saem_dfop_sfo_3) } } -- cgit v1.2.3