ggs_density: Density plots of the chains

In ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference

Description

Density plots with the parameter distribution. For multiple chains, use colours to differentiate the distributions.

Usage

ggs_density(D, family = NA, rug = FALSE, hpd = FALSE, greek = FALSE)

Arguments

D	Data frame whith the simulations.
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).
rug	Logical indicating whether a rug must be added to the plot. It is FALSE by default, since in large chains it may use lot of resources and it is not central to the plot.
hpd	Logical indicating whether HPD intervals (using the defaults from ci()) must be added to the plot. It is FALSE by default.
greek	Logical value indicating whether parameter labels have to be parsed to get Greek letters. Defaults to false.

Value

A ggplot object.

References

Fernández-i-Marín, 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

data(linear)
ggs_density(ggs(s))

Example output

Loading required package: dplyr

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Loading required package: tidyr
Loading required package: ggplot2

ggmcmc documentation built on Feb. 10, 2021, 5:10 p.m.