pmhtutorial: Minimal Working Examples for Particle Metropolis-Hastings

Routines for state estimate in a linear Gaussian state space model and a simple stochastic volatility model using particle filtering. Parameter inference is also carried out in these models using the particle Metropolis-Hastings algorithm that includes the particle filter to provided an unbiased estimator of the likelihood. This package is a collection of minimal working examples of these algorithms and is only meant for educational use and as a start for learning to them on your own.

Version: 1.2
Depends: R (≥ 3.2.3)
Imports: mvtnorm, Quandl, grDevices, graphics, stats
Published: 2017-10-07
Author: Johan Dahlin
Maintainer: Johan Dahlin <uni at>
License: GPL-2
NeedsCompilation: no
CRAN checks: pmhtutorial results


Reference manual: pmhtutorial.pdf
Package source: pmhtutorial_1.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: pmhtutorial_1.2.tgz, r-oldrel: pmhtutorial_1.2.tgz
Old sources: pmhtutorial archive


Please use the canonical form to link to this page.