plot.jsdmStanFit: Plot the traceplots and density plots for parameters within a...

In fseaton/jsdmstan: Fitting jSDMs in Stan

Plot the traceplots and density plots for parameters within a jsdmStanFit object

Description

This function takes parameters from the jsdmStanfit object and plots them using the bayesplot::mcmc_combo()function from the bayesplot package.

Usage

## S3 method for class 'jsdmStanFit'
plot(
  x,
  pars = NULL,
  combo = c("dens", "trace"),
  N = 5L,
  ask = TRUE,
  inc_warmup = FALSE,
  include = TRUE,
  sample_n = 10,
  regexp = FALSE,
  plot = TRUE,
  newpage = TRUE,
  ...
)

Arguments

x	The jsdmStanFit model object
pars	The parameters to plot, by default a random sample of twenty of the parameters fit within the model
combo	Which combination of plot types within bayesplot::mcmc_combo() to use, by default c("dens", "trace")
N	The number of plots per page, default 5
ask	Whether to ask before plotting a new page, default TRUE
inc_warmup	Whether to include the warmup period in the plots, by default FALSE
include	Whether to include or exclude the parameters specified by pars, by default TRUE (i.e. include)
sample_n	If pars = NULL then the number of random non-sigma parameters to include (details in description)
regexp	If pars should be treated as a regular expression for matching to parnames, by default FALSE
plot	Whether to plot the plots, default TRUE
newpage	Whether the first plot should be plotted on a new page, by default TRUE
...	Arguments passed to bayesplot::mcmc_combo()

Details

This acts as an interface to the bayesplot::mcmc_combo() function, with the default being to plot a density plot and a trace plot for each parameter specified, although this can be changed by setting the combo argument. These jSDM models have a lot of parameters so selecting a subset is recommended. If pars is set to NULL (the default) all parameters with either sigma or kappa in their name will be plotted along with a random selection of the other parameters (total number of other parameters set by sample_n). To see the name of the parameters within the model use get_parnames() - and if you want to plot all parameters (there will be hundreds in any reasonably sized model) set pars = get_parnames(x).

Value

An invisible list of the plots#

See Also

mcmc_plot.jsdmStanFit() for more plotting options.

Examples

## Not run: 
# First simulate data and get model fit:
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 plot:
plot(mglmm_fit)

# Plotting specifically the cor_species parameters:
plot(mglmm_fit, pars = "cor_species", regexp = TRUE)

# Increasing the number of randomly sampled parameters to plot:
plot(mglmm_fit, sample_n = 20)

## End(Not run)

fseaton/jsdmstan documentation built on Sept. 29, 2024, 6:40 p.m.