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

Downloads:

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

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