MSGARCH: Markov-Switching GARCH Models

Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.

Version: 2.42
Imports: Rcpp, coda, methods, zoo, expm, fanplot, MASS, numDeriv
LinkingTo: Rcpp, RcppArmadillo
Suggests: mcmc, testthat
Published: 2020-04-20
Author: David Ardia ORCID iD [aut], Keven Bluteau ORCID iD [aut, cre], Kris Boudt ORCID iD [ctb], Leopoldo Catania ORCID iD [aut], Alexios Ghalanos [ctb], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]
Maintainer: Keven Bluteau <Keven.Bluteau at hec.ca>
BugReports: https://github.com/keblu/MSGARCH/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: see file COPYRIGHTS
URL: https://github.com/keblu/MSGARCH
NeedsCompilation: yes
Citation: MSGARCH citation info
Materials: NEWS
In views: Finance
CRAN checks: MSGARCH results

Downloads:

Reference manual: MSGARCH.pdf
Package source: MSGARCH_2.42.tar.gz
Windows binaries: r-prerelease: MSGARCH_2.42.zip, r-release: MSGARCH_2.42.zip, r-oldrel: MSGARCH_2.42.zip
macOS binaries: r-prerelease: MSGARCH_2.31.tgz, r-release: MSGARCH_2.42.tgz, r-oldrel: MSGARCH_2.31.tgz
Old sources: MSGARCH archive

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