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: 1.0.0
Depends: R (≥ 3.2.3)
Imports: mvtnorm, Quandl, grDevices, graphics, stats
Published: 2016-01-19
Author: Johan Dahlin
Maintainer: Johan Dahlin <johan.dahlin at liu.se>
License: GPL-2
URL: https://github.com/compops/pmh-tutorial
NeedsCompilation: no
Materials: README NEWS
CRAN checks: pmhtutorial results

Downloads:

Reference manual: pmhtutorial.pdf
Package source: pmhtutorial_1.0.0.tar.gz
Windows binaries: r-devel: pmhtutorial_1.0.0.zip, r-release: pmhtutorial_1.0.0.zip, r-oldrel: pmhtutorial_1.0.0.zip
OS X El Capitan binaries: r-release: pmhtutorial_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: pmhtutorial_1.0.0.tgz

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