EMC2 (version 3.1.0)

plot_pars: Plots Density for Parameters

Description

Plots the posterior and prior density for selected parameters of a model. Full range of samples manipulations described in get_pars.

Usage

plot_pars(
  emc,
  layout = NA,
  selection = "mu",
  show_chains = FALSE,
  plot_prior = TRUE,
  N = 10000,
  use_prior_lim = !all_subjects,
  lpos = "topright",
  true_pars = NULL,
  all_subjects = FALSE,
  prior_args = list(),
  true_args = list(),
  ...
)

Value

An invisible return of the contraction statistics for the selected parameter type

Arguments

emc

An emc object

layout

A vector indicating which layout to use as in par(mfrow = layout). If NA, will automatically generate an appropriate layout.

selection

A Character string. Indicates which parameter type to use (e.g., alpha, mu, sigma2, correlation).

show_chains

Boolean (defaults to FALSE) plots a separate density for each chain.

plot_prior

Boolean. If TRUE will overlay prior density in the plot (default in red)

N

Integer. How many prior samples to draw

use_prior_lim

Boolean. If TRUE will use xlimits based on prior density, otherwise based on posterior density.

lpos

Character. Where to plot the contraction statistic.

true_pars

A vector or emc object. Can be used to visualize recovery. If a vector will plot a vertical line for each parameter at the appropriate place. If an emc object will plot the densities of the object as well, assumed to be the data-generating posteriors.

all_subjects

Boolean. Will plot the densities of all (selected) subjects overlaid with the group-level distribution

prior_args

A list. Optional additional arguments to be passed to plot.default for the plotting of the prior density (see par())

true_args

A list. Optional additional arguments to be passed to plot.default for the plotting of the true parameters (see par())

...

Optional arguments that can be passed to get_pars, density, or plot.default (see par())

Examples

# Full range of possibilities described in get_pars
plot_pars(samples_LNR)
# Or plot all subjects
plot_pars(samples_LNR, all_subjects = TRUE, col = 'purple')
# Or plot recovery
true_emc <- samples_LNR # This would normally be the data-generating samples
plot_pars(samples_LNR, true_pars = true_emc, true_args = list(col = 'blue'), adjust = 2)