BayesianTools (version 0.1.3)

marginalPlot: Plot MCMC marginals

Description

Plot MCMC marginals

Usage

marginalPlot(mat, thin = "auto", scale = NULL, best = NULL, ...)

Arguments

mat

object of class "bayesianOutput" or a matrix or data frame of variables

thin

thinning of the matrix to make things faster. Default is to thin to 5000

scale

should the results be scaled. Value can be either NULL (no scaling), T, or a matrix with upper / lower bounds as columns. If set to T, attempts to retrieve the scaling from the input object mat (requires that this is of class BayesianOutput)

best

if provided, will draw points at the given values (to display true / default parameter values). Value can be either NULL (no drawing), a vector with values, or T, in which case the function will attempt to retrieve the values from a BayesianOutput

...

additional parameters to pass on to the getSample

See Also

plotTimeSeries tracePlot correlationPlot

Examples

# NOT RUN {
dat = generateTestDensityMultiNormal(n = 100000, sample = TRUE)
marginalPlot(dat(10000))
# }