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 johandahlin.com>
License:	GPL-2
URL:	https://github.com/compops/pmh-tutorial-rpkg
NeedsCompilation:	no
Citation:	pmhtutorial citation info
CRAN checks:	pmhtutorial results

Documentation:

Reference manual:

pmhtutorial.pdf

Downloads:

Package source:	pmhtutorial_1.5.tar.gz
Windows binaries:	r-devel: pmhtutorial_1.5.zip, r-release: pmhtutorial_1.5.zip, r-oldrel: pmhtutorial_1.5.zip
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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