post.pred.check: post.pred.check

In bayesanova: Bayesian Inference in the Analysis of Variance via Markov Chain Monte Carlo in Gaussian Mixture Models

post.pred.check

Description

Provides a posterior predictive check for a fitted Bayesian ANOVA model.

Usage

post.pred.check(anovafit, ngroups, out, reps = 50, eta)

Arguments

anovafit	A dataframe returned by bayes.anova
ngroups	An integer which is the number of groups used in the ANOVA
out	A numerical vector containing the originally observed data in all groups
reps	An integer which is the number of posterior predictive distributions sampled from the ANOVA models posterior distribution. Defaults to 50 sampled parameters.
eta	A numerical vector containing the weight values of the mixture.

Details

Provides a posterior predictive check for a fitted Bayesian ANOVA model.

Value

Produces a plot consisting of a density estimate of the original data and posterior predictive distributions sampled from the posterior of the Bayesian ANOVA model as density overlays.

Author(s)

Riko Kelter

Examples

set.seed(700)
x1=rnorm(1000,0,1)
x2=rnorm(1000,1,1)
x3=rnorm(1000,2,2)

result=bayes.anova(n=1000,first = x1, second=x2, third=x3)
post.pred.check(result, ngroups = 3, out = c(x1,x2,x3), reps = 25, eta = c(1/3,1/3,1/3))

bayesanova documentation built on May 29, 2024, 5:38 a.m.