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: 1.5
Depends: R (≥ 3.2.3)
Imports: mvtnorm, Quandl, grDevices, graphics, stats
Published: 2019-03-22
DOI: 10.32614/CRAN.package.pmhtutorial
Author: Johan Dahlin
Maintainer: Johan Dahlin <uni at>
License: GPL-2
NeedsCompilation: no
Citation: pmhtutorial citation info
CRAN checks: pmhtutorial results


Reference manual: pmhtutorial.pdf


Package source: pmhtutorial_1.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): pmhtutorial_1.5.tgz, r-oldrel (arm64): pmhtutorial_1.5.tgz, r-release (x86_64): pmhtutorial_1.5.tgz, r-oldrel (x86_64): pmhtutorial_1.5.tgz
Old sources: pmhtutorial archive


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