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.

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
https://github.com/compops/pmh-tutorial

View on CRAN

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.