ggmcmc (version 1.5.1.1)

ggs_ppmean: Posterior predictive plot comparing the outcome mean vs the distribution of the predicted posterior means.

Description

Histogram with the distribution of the predicted posterior means, compared with the mean of the observed outcome.

Usage

ggs_ppmean(D, outcome, family = NA, bins = 30)

Arguments

D

Data frame whith the simulations. Notice that only the posterior outcomes are needed, and so either the ggs() call limits the parameters to the outcomes or the user provides a family of parameters to limit it.

outcome

vector (or matrix or array) containing the observed outcome variable. Currently only a vector is supported.

family

Name of the family of parameters to plot, as given by a character vector or a regular expression. A family of parameters is considered to be any group of parameters with the same name but different numerical value between square brackets (as beta[1], beta[2], etc).

bins

integer indicating the total number of bins in which to divide the histogram. Defaults to 30, which is the same as geom_histogram()

Value

A ggplot object.

References

Fern<U+00E1>ndez-i-Mar<U+00ED>n, Xavier (2016) ggmcmc: Analysis of MCMC Samples and Bayesian Inference. Journal of Statistical Software, 70(9), 1-20. doi:10.18637/jss.v070.i09

Examples

# NOT RUN {
data(linear)
ggs_ppmean(ggs(s.y.rep), outcome=y)
# }