plot.Rd 1.65 KB
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% plot.mcmcabn.Rd ---
% Author           : Gilles Kratzer
% Created on :       18.02.2019
% Last modification :
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

\name{plot.mcmcabn}
\alias{plot.mcmcabn}
\title{Function to MCMC samples generated by mcmcabn}

\usage{
\method{plot}{mcmcabn}(x,
     max.score = FALSE,
     \dots)
     }

\arguments{
  \item{x}{object of class mcmcabn.}
  \item{max.score}{logical to plot the cumulative maximum network score.}
  \item{\dots}{arguments to be passed to methods}
  }

\description{plot method for mcmcabn objects.
}

\details{The plot function for mcmcabn objects is based on ggplot2, ggpubr and cowplot. By default it return a trace plot with coloured points when MBR and REV methods have been used. It has histograms on the right of the densities of MC3, MBR and REV MCMC jumps respectively.}

\author{Gilles Kratzer}

\references{
H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016.

Alboukadel Kassambara (2018). ggpubr: 'ggplot2' Based Publication Ready Plots. R package version 0.2. https://CRAN.R-project.org/package=ggpubr

Claus O. Wilke (2019). cowplot: Streamlined Plot Theme and Plot Annotations for 'ggplot2'. R package version 0.9.4. https://CRAN.R-project.org/package=cowplot

Scutari, M. (2010). Learning Bayesian Networks with the bnlearn R Package. Journal of Statistical Software, 35(3), 1 - 22. doi:http://dx.doi.org/10.18637/jss.v035.i03.
}

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\examples{
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\dontrun{
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## Example from the asia dataset from Lauritzen and Spiegelhalter (1988) provided by Scutari (2010)
data("mcmc_run_asia")

#plot the mcmc run
plot(mcmc.out)
}}