pmhtutorial: Minimal Working Examples for Particle Metropolis-Hastings
Version 1.0.0

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.

Package details

AuthorJohan Dahlin <johan.dahlin@liu.se>
Date of publication2016-01-19 18:04:57
MaintainerJohan Dahlin <johan.dahlin@liu.se>
LicenseGPL-2
Version1.0.0
URL https://github.com/compops/pmh-tutorial
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("pmhtutorial")

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pmhtutorial documentation built on May 29, 2017, 10:45 a.m.