plot_ibbu_stanfit_parameter_correlations: Plot correlations between IBBU parameters.

In hlplab/MVBeliefUpdatr: Fitting, Summarizing, and Visualizing of Multivariate Gaussian Ideal Observers and Adaptors

Plot correlations between IBBU parameters.

Description

Plot correlations between post-warmup MCMC samples for all parameters representing the prior and/or posterior beliefs.

Usage

plot_ibbu_stanfit_parameter_correlations(
  model,
  categories = get_category_levels_from_stanfit(model),
  groups = "prior",
  cues = get_cue_levels_from_stanfit(model),
  pars = NULL,
  ndraws = NULL,
  untransform_cues = TRUE,
  category.colors = get_default_colors("category", categories)
)

Arguments

model	mv-ibbu-stanfit object.
categories, groups, cues, pars	Character vector of categories, groups, cues, and/or parameters to be plotted. To subset to specific parameters, note the following naming conventions: (1) all 'm' parameters are named 'm_cue_name' (2) the 'S' parameter is decomposed into a vector of standard deviations 'tau' and a correlation matrix 'rho'. (3) all 'tau' parameters are named 'tau_cue_name' (4) all 'rho' parameters are named 'rho_cue_name1__x__cue_name2' (default: all categories, cues, and parameters in the model; '"prior"' for group since those are the only free parameters).
ndraws	Number of draws to plot (or use to calculate the CIs), or 'NULL' if all draws are to be returned. (default: 'NULL')
untransform_cues	Should m_0 and S_0 be transformed back into the original cue space? (default: 'TRUE')
category.colors	Vector of fill colors of same length as category or 'NULL' to use defaults. (default: 'NULL')

Details

Typically, the categories, groups, and cues are automatically added to the fit during the creation of the fit. If necessary, however, it is possible to use recover_types on the stanfit object to add or change these levels later.

Value

ggplot object.

See Also

TBD

hlplab/MVBeliefUpdatr documentation built on March 29, 2025, 10:42 p.m.