paratraceplot.svdraws: Trace Plot of MCMC Draws from the Parameter Posteriors

In gregorkastner/stochvol: Efficient Bayesian Inference for Stochastic Volatility (SV) Models

Trace Plot of MCMC Draws from the Parameter Posteriors

Description

Displays a plot of iterations vs. sampled values the parameters mu, phi, sigma (and potentially nu or rho), with a separate plot per variable.

Usage

## S3 method for class 'svdraws'
paratraceplot(
  x,
  mar = c(1.9, 1.9, 1.9, 0.5),
  mgp = c(2, 0.6, 0),
  simobj = NULL,
  ...
)

Arguments

x	svdraws object.
mar	numerical vector of length 4, indicating the plot margins. See par for details. The default value is c(1.9, 1.9, 1.9, 0.5), which is slightly smaller than the R-defaults.
mgp	numerical vector of length 3, indicating the axis and label positions. See par for details. The default value is c(2, 0.6, 0), which is slightly smaller than the R-defaults.
simobj	object of class svsim as returned by the SV simulation function svsim. If provided, “true” data generating values will be added to the plots.
...	further arguments are passed on to the invoked matplot function.

Details

paratraceplot is modeled after traceplot in the coda package, with very minor modifications.

Value

Called for its side effects. Returns argument x invisibly.

Note

You can call this function directly, but it is more commonly called by the plot.svdraws method.

See Also

Other plotting: paradensplot(), paratraceplot(), plot.svdraws(), plot.svpredict(), volplot()

gregorkastner/stochvol documentation built on March 7, 2024, 8:46 p.m.