mcmc_plot.brmcoda: MCMC Plots Implemented in 'bayesplot'

In florale/multilevelcoda: Estimate Bayesian Multilevel Models for Compositional Data

MCMC Plots Implemented in bayesplot

Description

Call MCMC plotting functions implemented in the bayesplot package.

Usage

## S3 method for class 'brmcoda'
mcmc_plot(object, ...)

Arguments

object	A brmcoda class object.
...	Further arguments passed to mcmc_plot.brmsfit.

Value

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

See Also

mcmc_plot.brmsfit

Examples

## Not run: 
cilr <- compilr(data = mcompd, sbp = sbp,
        parts = c("TST", "WAKE", "MVPA", "LPA", "SB"), idvar = "ID")

# model with compositional predictor at between and within-person levels
fit <- brmcoda(compilr = cilr,
               formula = Stress ~ bilr1 + bilr2 + bilr3 + bilr4 +
                                 wilr1 + wilr2 + wilr3 + wilr4 + (1 | ID),
               chain = 1, iter = 500)
mcmc_plot(fit)

## End(Not run)

florale/multilevelcoda documentation built on April 21, 2024, 9:44 a.m.