From a54bd290bc3884d0000c52c1b29bc557825d9eae Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 15 Dec 2022 14:50:28 +0100 Subject: List random effects correlations in output if any Update docs --- NEWS.md | 4 +- R/intervals.R | 8 +- R/summary.saem.mmkin.R | 16 +- docs/dev/index.html | 21 +- docs/dev/news/index.html | 57 +++- docs/dev/pkgdown.yml | 4 +- docs/dev/reference/Rplot001.png | Bin 18113 -> 1011 bytes docs/dev/reference/Rplot002.png | Bin 38732 -> 16953 bytes docs/dev/reference/illparms.html | 15 +- docs/dev/reference/parplot.html | 9 +- docs/dev/reference/saem.html | 21 +- docs/dev/reference/summary.saem.mmkin.html | 508 ++++++++++++++++------------- log/test.log | 20 +- man/summary.saem.mmkin.Rd | 13 +- 14 files changed, 422 insertions(+), 274 deletions(-) diff --git a/NEWS.md b/NEWS.md index 4540b517..7e65204f 100644 --- a/NEWS.md +++ b/NEWS.md @@ -2,7 +2,7 @@ - '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. @@ -10,6 +10,8 @@ - '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) - '{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/R/intervals.R b/R/intervals.R index 705ef6eb..fcdbaea9 100644 --- a/R/intervals.R +++ b/R/intervals.R @@ -78,8 +78,12 @@ intervals.saem.mmkin <- function(object, level = 0.95, backtransform = TRUE, ... # Random effects sdnames <- intersect(rownames(conf.int), paste("SD", pnames, sep = ".")) - ranef_ret <- as.matrix(conf.int[sdnames, c("lower", "est.", "upper")]) - rownames(ranef_ret) <- paste0(gsub("SD\\.", "sd(", sdnames), ")") + corrnames <- grep("^Corr.", rownames(conf.int), value = TRUE) + ranef_ret <- as.matrix(conf.int[c(sdnames, corrnames), c("lower", "est.", "upper")]) + sdnames_ret <- paste0(gsub("SD\\.", "sd(", sdnames), ")") + corrnames_ret <- gsub("Corr\\.(.*)\\.(.*)", "corr(\\1,\\2)", corrnames) + rownames(ranef_ret) <- c(sdnames_ret, corrnames_ret) + attr(ranef_ret, "label") <- "Random effects:" diff --git a/R/summary.saem.mmkin.R b/R/summary.saem.mmkin.R index 46ab548b..49b02a50 100644 --- a/R/summary.saem.mmkin.R +++ b/R/summary.saem.mmkin.R @@ -75,10 +75,21 @@ #' 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) #' } #' #' @export @@ -150,7 +161,8 @@ summary.saem.mmkin <- function(object, data = FALSE, verbose = FALSE, distimes = # Random effects sdnames <- intersect(rownames(conf.int), paste0("SD.", pnames)) - confint_ranef <- as.matrix(conf.int[sdnames, c("estimate", "lower", "upper")]) + corrnames <- grep("^Corr.", rownames(conf.int), value = TRUE) + confint_ranef <- as.matrix(conf.int[c(sdnames, corrnames), c("estimate", "lower", "upper")]) colnames(confint_ranef)[1] <- "est." # Error model diff --git a/docs/dev/index.html b/docs/dev/index.html index 2615d389..4723879e 100644 --- a/docs/dev/index.html +++ b/docs/dev/index.html @@ -222,12 +222,21 @@

References

- - - + + + + + + + + +
Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. Environments 8 (8) 71 doi:10.3390/environments8080071 -
Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data Environments 6 (12) 124 doi:10.3390/environments6120124 -
Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data Environmental Sciences Europe 30 17 doi:10.1186/s12302-018-0145-1 -
+Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. Environments 8 (8) 71 doi:10.3390/environments8080071 +
+Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data Environments 6 (12) 124 doi:10.3390/environments6120124 +
+Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data Environmental Sciences Europe 30 17 doi:10.1186/s12302-018-0145-1 +
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”
+

mkin 1.0.4 (2021-04-20)

mkin 1.0.3 (2021-02-15)

-
+

mkin 1.0.2 (Unreleased)

-
+

mkin 1.0.1 (2021-02-10)

mkin 0.9.49.11 (2020-04-20)

-
+

mkin 0.9.49.10 (2020-04-18)

mkin 0.9.46 (2017-07-24)

-
+

mkin 0.9.45.2 (2017-07-24)

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
+

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
+

Minor changes

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. +

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

-
+

mkin 0.9-35 (2015-05-15)

Major changes

-
  • Switch from RUnit to testthat for testing
+

Bug fixes

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().
+

Major changes

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 v1.2.1