# post.pred.check: post.pred.check In bayesanova: Bayesian Inference in the Analysis of Variance via Markov Chain Monte Carlo in Gaussian Mixture Models

## Description

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

## Usage

 `1` ```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.

Riko Kelter

## Examples

 ```1 2 3 4 5 6 7``` ```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)) ```

### Example output

```Bayesian ANOVA output:
Details: Gaussian-mixture model with three components

|Parameter     |LQ    |Mean  |UQ    |Std.Err |
|:-------------|:-----|:-----|:-----|:-------|
|mu1           |-0.05 |-0.05 |-0.04 |0       |
|mu2           |1.02  |1.02  |1.03  |0       |
|mu3           |2.1   |2.11  |2.12  |0       |
|sigma1        |1.05  |1.09  |1.14  |0.02    |
|sigma2        |1.05  |1.1   |1.14  |0.02    |
|sigma3        |1.98  |2.07  |2.17  |0.05    |
|mu2-mu1       |1.07  |1.07  |1.07  |0       |
|mu3-mu1       |2.15  |2.16  |2.17  |0       |
|mu3-mu2       |1.08  |1.09  |1.1   |0       |
|sigma2-sigma1 |-0.06 |0     |0.07  |0.03    |
|sigma3-sigma1 |0.88  |0.98  |1.09  |0.05    |
|sigma3-sigma2 |0.88  |0.98  |1.09  |0.05    |
|delta12       |-1.04 |-1.02 |-1.01 |0.01    |
|delta13       |-1.74 |-1.72 |-1.68 |0.01    |
|delta23       |-0.88 |-0.86 |-0.85 |0.01    |
```

bayesanova documentation built on July 2, 2020, 2:29 a.m.