bayesSSM: Bayesian Methods for State Space Models

Implements methods for Bayesian analysis of State Space Models. Includes implementations the Particle Marginal Metropolis-Hastings algorithm described in Andrieu et al. (2010) <doi:10.1111/j.1467-9868.2009.00736.x> and automatic tuning inspired by Pitt et al. (2012) <doi:10.1016/j.jeconom.2012.06.004> and J. Dahlin and T. B. Schön (2019) <doi:10.18637/jss.v088.c02>.

Version:	0.4.7
Imports:	MASS, stats, dplyr, future, future.apply
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), ggplot2, tidyr, extraDistr
Published:	2025-04-23
DOI:	10.32614/CRAN.package.bayesSSM
Author:	Bjarke Hautop [aut, cre, cph]
Maintainer:	Bjarke Hautop <bjarke.hautop at gmail.com>
BugReports:	https://github.com/BjarkeHautop/bayesSSM/issues
License:	MIT + file LICENSE
URL:	https://github.com/BjarkeHautop/bayesSSM, https://bjarkehautop.github.io/bayesSSM/
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	bayesSSM results

Documentation:

Reference manual:	bayesSSM.pdf
Vignettes:	bayesSSM (source, R code)

Downloads:

Package source:	bayesSSM_0.4.7.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): bayesSSM_0.4.7.tgz, r-oldrel (arm64): bayesSSM_0.4.7.tgz, r-release (x86_64): bayesSSM_0.4.7.tgz, r-oldrel (x86_64): bayesSSM_0.4.7.tgz

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