StatsPlots.jl

MCMCChains implements many functions for plotting via StatsPlots.jl.

Simple example

The following simple example illustrates how to use Chain to visually summarize a MCMC simulation:

using MCMCChains
using StatsPlots

# Define the experiment
n_iter = 100
n_name = 3
n_chain = 2

# experiment results
val = randn(n_iter, n_name, n_chain) .+ [1, 2, 3]'
val = hcat(val, rand(1:2, n_iter, 1, n_chain))

# construct a Chains object
chn = Chains(val, [:A, :B, :C, :D])

# visualize the MCMC simulation results
plot(chn; size=(840, 600))

┌ Warning: seriestype density has been moved to StatsPlots.  To use: `Pkg.add("StatsPlots"); using StatsPlots`
└ @ Plots ~/.julia/packages/Plots/kyYZF/src/args.jl:1189
┌ Warning: seriestype density has been moved to StatsPlots.  To use: `Pkg.add("StatsPlots"); using StatsPlots`
└ @ Plots ~/.julia/packages/Plots/kyYZF/src/args.jl:1189
┌ Warning: seriestype density has been moved to StatsPlots.  To use: `Pkg.add("StatsPlots"); using StatsPlots`
└ @ Plots ~/.julia/packages/Plots/kyYZF/src/args.jl:1189
┌ Warning: seriestype density has been moved to StatsPlots.  To use: `Pkg.add("StatsPlots"); using StatsPlots`
└ @ Plots ~/.julia/packages/Plots/kyYZF/src/args.jl:1189
┌ Warning: seriestype density has been moved to StatsPlots.  To use: `Pkg.add("StatsPlots"); using StatsPlots`
└ @ Plots ~/.julia/packages/Plots/kyYZF/src/args.jl:1189
┌ Warning: seriestype density has been moved to StatsPlots.  To use: `Pkg.add("StatsPlots"); using StatsPlots`
└ @ Plots ~/.julia/packages/Plots/kyYZF/src/args.jl:1189

plot(chn, colordim = :parameter; size=(840, 400))

Note that the plot function takes the additional arguments described in the Plots.jl package.

Mixed density

plot(chn, seriestype = :mixeddensity)

Or, for all seriestypes, use the alternative shorthand syntax:

mixeddensity(chn)

Trace

plot(chn, seriestype = :traceplot)

traceplot(chn)

Running average

meanplot(chn)

Density

density(chn)

Histogram

histogram(chn)

Autocorrelation

autocorplot(chn)

Corner

corner(chn)