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: 3.0.3
Depends: R (≥ 2.0), numDeriv, coda
Published: 2021-10-05
Author: Jose Augusto Fiorucci ORCID iD [aut, cre, cph], Ricardo Sanders Ehlers ORCID iD [aut, cph], Francisco Louzada ORCID iD [aut, cph]
Maintainer: Jose Augusto Fiorucci <jafiorucci at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: README ChangeLog
CRAN checks: bayesDccGarch results


Reference manual: bayesDccGarch.pdf


Package source: bayesDccGarch_3.0.3.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): bayesDccGarch_3.0.3.tgz, r-release (x86_64): bayesDccGarch_3.0.3.tgz, r-oldrel: bayesDccGarch_3.0.3.tgz
Old sources: bayesDccGarch archive


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