makePlotsParticleMetropolisHastingsSVModel {pmhtutorial}

Make plots for tutorial

Description

Creates diagnoistic plots from runs of the particle Metropolis-Hastings algorithm.

Usage

makePlotsParticleMetropolisHastingsSVModel(y, res, noBurnInIterations,
  noIterations, nPlot)

Arguments

y

Observations from the model for t=1,...,T.

res

The output from a run of particleMetropolisHastings, particleMetropolisHastingsSVmodel or particleMetropolisHastingsSVmodelReparameterised.

noBurnInIterations

The number of burn-in iterations in the PMH algorithm. Must be smaller than noIterations.

noIterations

The number of iterations in the PMH algorithm.

nPlot

Number of steps in the Markov chain to plot.

Value

The function returns plots similar to the ones in the reference as well as the estimate of the integrated autocorrelation time for each parameter.

Author(s)

Johan Dahlin [e-mail]

References

Dahlin, J. & Schon, T. B. "Getting Started with Particle Metropolis-Hastings for Inference in Nonlinear Dynamical Models." Journal of Statistical Software, Code Snippets, 88(2): 1–41, 2019.