Description Usage Arguments Details Value Author(s) Examples
Provides a posterior predictive check for a fitted Bayesian ANOVA model.
1 | post.pred.check(anovafit, ngroups, out, reps = 50, eta)
|
anovafit |
A dataframe returned by |
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. |
Provides a posterior predictive check for a fitted Bayesian ANOVA model.
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
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))
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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 |
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