ggs_traceplot: Traceplot of the chains

In ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference

Description

Traceplot with the time series of the chains.

Usage

ggs_traceplot(
  D,
  family = NA,
  original_burnin = TRUE,
  original_thin = TRUE,
  simplify = NULL,
  hpd = FALSE,
  greek = FALSE
)

Arguments

D	Data frame with 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).
original_burnin	Logical. When TRUE (the default) start the Iteration counter in the x-axis at the end of the burnin period.
original_thin	Logical. When TRUE (the default) take into account the thinning interval in the x-axis.
simplify	Numerical. A percentage of iterations to keep in the time series. It is an option intended only for the purpose of saving time and resources when doing traceplots. It is not a thin operation, because it is not regular. It must be used with care.
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_traceplot(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.