bayesDccGarch: Methods and Tools for Bayesian Dynamic Conditional Correlation GARCH(1,1) Model

Bayesian estimation of dynamic conditional correlation GARCH model for multivariate time series volatility (Fioruci, J.A., Ehlers, R.S. and Andrade-Filho, M.G., (2014). <doi:10.1080/02664763.2013.839635>.

Version:	3.0.4
Depends:	R (≥ 2.0), numDeriv, coda
Published:	2023-04-22
DOI:	10.32614/CRAN.package.bayesDccGarch
Author:	Jose Augusto Fiorucci [aut, cre, cph], Ricardo Sanders Ehlers [aut, cph], Francisco Louzada [aut, cph]
Maintainer:	Jose Augusto Fiorucci <jafiorucci at gmail.com>
BugReports:	https://github.com/jafiorucci/bayesDccGarch/issues
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL:	https://ui.adsabs.harvard.edu/abs/2014arXiv1412.2967F/abstract
NeedsCompilation:	yes
Materials:	README, ChangeLog
In views:	Bayesian
CRAN checks:	bayesDccGarch results

Documentation:

Reference manual:

bayesDccGarch.html , bayesDccGarch.pdf

Downloads:

Package source:	bayesDccGarch_3.0.4.tar.gz
Windows binaries:	r-devel: bayesDccGarch_3.0.4.zip, r-release: bayesDccGarch_3.0.4.zip, r-oldrel: bayesDccGarch_3.0.4.zip
macOS binaries:	r-release (arm64): bayesDccGarch_3.0.4.tgz, r-oldrel (arm64): bayesDccGarch_3.0.4.tgz, r-release (x86_64): bayesDccGarch_3.0.4.tgz, r-oldrel (x86_64): bayesDccGarch_3.0.4.tgz
Old sources:	bayesDccGarch archive

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