Posterior predictive checks for jsdmStanFit objects — pp

This function acts as an interface to bayesplot::pp_check(), by default calculating summary statistics for each site (i.e. row in the response matrix) which are then plotted and compared to the data used to fit the model.

Usage

# S3 method for class 'jsdmStanFit'
pp_check(
  object,
  plotfun = "dens_overlay",
  species = NULL,
  sites = NULL,
  summary_stat = "sum",
  calc_over = "site",
  ndraws = NULL,
  ...
)

Arguments

object: An object of class jsdmStanFit
plotfun: The ppc plot function to use, given as a character string. The default is to call ppc_dens_overlay. Can be specified as either the entire name of function as a character string or without the ppc_ prefix. If plotfun == "pairs" then a pairs plot is produced with a diagonal of density plots for the selected species, the upper triangle showing the recovery of the correlation between the selected species, and the lower triangle showing the plotted relationships between the species in the data and one draw of the posterior prediction.
species: Which species to include in the summary statistic, by default all
sites: Which sites to include in the summary statistic, by default all
summary_stat: The summary statistic to be used, by default sum but any function can be used.
calc_over: Whether to calculate the summary statistic by site or species, by default species
ndraws: Number of draws, by default the number of samples in the posterior. Will be sampled randomly from the chains if fewer than the number of samples.
...: Additional arguments passed to jsdm_statsummary().

Value

A ggplot object that can be further customised using the ggplot2 package.

Details

This function takes a jsdmStanFit object and tries to extract statistics that can give useful summaries within a posterior prediction (or retrodiction) using the bayesplot::pp_check() function. It uses the jsdm_statsummary() function to get summary statistics and then supplies them to the specified ppc_ function from the bayesplot package. For a full list of available plotting functions call bayesplot::available_ppc().

Examples

if (FALSE) { # \dontrun{
# First simulate data and fit the jsdmStan model:
mglmm_data <- mglmm_sim_data(
  N = 100, S = 10, K = 3,
  family = "gaussian"
)
mglmm_fit <- stan_mglmm(
  Y = mglmm_data$Y, X = mglmm_data$X,
  family = "gaussian"
)

# The default is to plot a density overlay:
pp_check(mglmm_fit)

# Other plot functions can be called, such as a ribbon plot:
pp_check(mglmm_fit, plotfun = "ribbon")

# Instead of calculating the sum over sites other statistics can be calculated,
# e.g. the mean of each species:
pp_check(mglmm_fit,
  plotfun = "ecdf_overlay", summary_stat = "mean",
  calc_over = "species", ndraws = 20
)

# A pairs plot - limiting to only a subset of species for graphical simplicity
pp_check(mglmm_fit, plotfun = "pairs", species = 1:4)
} # }