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. (2017) <https://ssrn.com/abstract=2845809>.

Version: 2.0
Imports: Rcpp, coda, methods, zoo, expm, fanplot, MASS, numDeriv
LinkingTo: Rcpp, RcppArmadillo
Suggests: mcmc, testthat
Published: 2017-11-16
Author: David Ardia [aut], Keven Bluteau [aut, cre], Kris Boudt [ctb], Leopoldo Catania [aut], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]
Maintainer: Keven Bluteau <Keven.Bluteau at unine.ch>
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_2.0.tar.gz
Windows binaries: r-devel: MSGARCH_2.0.zip, r-release: MSGARCH_2.0.zip, r-oldrel: MSGARCH_2.0.zip
OS X El Capitan binaries: r-release: MSGARCH_2.0.tgz
OS X Mavericks binaries: r-oldrel: MSGARCH_2.0.tgz
Old sources: MSGARCH archive

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