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Diffstat (limited to 'vignettes/web_only/multistart.rmd')
| -rw-r--r-- | vignettes/web_only/multistart.rmd | 31 |
1 files changed, 14 insertions, 17 deletions
diff --git a/vignettes/web_only/multistart.rmd b/vignettes/web_only/multistart.rmd index 27a8a96a..ccf26b3d 100644 --- a/vignettes/web_only/multistart.rmd +++ b/vignettes/web_only/multistart.rmd @@ -1,7 +1,7 @@ --- title: Short demo of the multistart method author: Johannes Ranke -date: Last change 26 September 2022 (rebuilt `r Sys.Date()`) +date: Last change 17 April 2023 (rebuilt `r Sys.Date()`) output: html_document vignette: > @@ -39,8 +39,8 @@ of 'log_k2' includes zero. We check this assessment using multiple runs with different starting values. ```{r} -f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16) -parplot(f_saem_full_multi) +f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 8) +parplot(f_saem_full_multi, lpos = "topleft") ``` This confirms that the variance of k2 is the most problematic parameter, so we @@ -50,8 +50,8 @@ for k2. ```{r} f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2") illparms(f_saem_reduced) -f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cores = 16) -parplot(f_saem_reduced_multi, lpos = "topright") +f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cores = 8) +parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2)) ``` The results confirm that all remaining parameters can be determined with sufficient @@ -63,20 +63,17 @@ We can also analyse the log-likelihoods obtained in the multiple runs: llhist(f_saem_reduced_multi) ``` -The parameter histograms can be further improved by excluding the result with -the low likelihood. +We can use the `anova` method to compare the models. ```{r} -parplot(f_saem_reduced_multi, lpos = "topright", llmin = -326, ylim = c(0.5, 2)) +anova(f_saem_full, best(f_saem_full_multi), + f_saem_reduced, best(f_saem_reduced_multi), test = TRUE) ``` -We can use the `anova` method to compare the models, including a likelihood ratio -test if the models are nested. - -```{r} -anova(f_saem_full, best(f_saem_reduced_multi), test = TRUE) -``` - -While AIC and BIC are lower for the reduced model, the likelihood ratio test -does not indicate a significant difference between the fits. +The reduced model results in lower AIC and BIC values, so it +is clearly preferable. Using multiple starting values gives +a large improvement in case of the full model, because it is +less well-defined, which impedes convergence. For the reduced +model, using multiple starting values only results in a small +improvement of the model fit. |