bayesplot: bayesian convergence diagnosis plotting function

In fcirt: Forced Choice in Item Response Theory

Description

This function provides plots including density plots, trace plots, and auto-correlation plots to aid model convergence diagnosis.

Usage

bayesplot(x, pars, plot, inc_warmup = FALSE)

Arguments

x	returned object
pars	Names of plotted parameters. They can be "theta", "alpha", "delta", "tau", or a subset of parameters. See vignette for fcirt for more details.
plot	Types of plots.They can be "density", "trace", or "autocorrelation".
inc_warmup	Whether to include warmup iterations or not when plotting. The default is FALSE.

Value

Selected plots for selected parameters

Examples

Data <- c(1)
Data <- matrix(Data,nrow = 1)
pairmap <- c(1,2)
pairmap <- matrix(pairmap,nrow = 1)
ind <- c(1,2)
ParInits <- c(1, 1, 1, -1, -1, -1)
ParInits <- matrix(ParInits, ncol = 3)
mod <- fcirt(fcirt.Data=Data,pairmap=pairmap,ind=ind,ParInits=ParInits,iter=3,warmup=1,chains=1)
bayesplot(mod, 'alpha', 'density', inc_warmup=FALSE)

fcirt documentation built on Feb. 2, 2022, 1:07 a.m.