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pmhtutorial  

Minimal Working Examples for Particle Metropolis-Hastings
View on CRAN: Click here


Download and install pmhtutorial package within the R console
Install from CRAN:
install.packages("pmhtutorial")

Install from Github:
library("remotes")
install_github("cran/pmhtutorial")

Install by package version:
library("remotes")
install_version("pmhtutorial", "1.5")



Attach the package and use:
library("pmhtutorial")
Maintained by
Johan Dahlin
[Scholar Profile | Author Map]
First Published: 2016-01-19
Latest Update: 2019-03-22
Description:
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.
How to cite:
Johan Dahlin (2016). pmhtutorial: Minimal Working Examples for Particle Metropolis-Hastings. R package version 1.5, https://cran.r-project.org/web/packages/pmhtutorial. Accessed 05 May. 2025.
Previous versions and publish date:
1.0.0 (2016-01-19 18:04), 1.2 (2017-10-07 16:34), 1.3 (2018-10-18 14:00), 1.4 (2019-01-11 16:10)
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Complete documentation for pmhtutorial
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