check_model.fit_model_bh_variance_intraR/plot.check_model_bh_variance_intra.R
plot.check_model_bh_variance_intra.Rdplot.check_model_bh_variance_intra returns ggplot to visualize outputs from check_model.fit_model_bh_variance_intra
# S3 method for check_model_bh_variance_intra plot(x, nb_parameters_per_plot = 10, ...)
| x | Output from |
|---|---|
| nb_parameters_per_plot | number of parameter per plot to display |
| ... | further arguments passed to or from other methods |
mu_ijk : distribution of each mu_ijk.
There are as many graph as needed with nb_parameters_per_plot alpha_i per graph.
sigma_ij : distribution of each sigma_ij.
There are as many graph as needed with nb_parameters_per_plot alpha_i per graph.
mcmc_not_converge_traceplot_density : a list with the plots of trace and density to check the convergence of the two MCMC only for chains that are not converging thanks to the Gelman-Rubin test. If all the chains converge, it is NULL.
S3 method.
For mcmc_not_converge_traceplot_density : If you wish exhaustive information, look at ggmcmc::ggmcmc with ggmcmc(out_model$MCMC).
But be careful with the size of your MCMC output which are often too big to be performed in R.
See example in the book: https://priviere.github.io/PPBstats_book/family-4.html#variance-intra