BayesBEKK: Bayesian Estimation of Bivariate Volatility Model

The Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) models are used for modelling the volatile multivariate data sets. In this package a variant of MGARCH called BEKK (Baba, Engle, Kraft, Kroner) proposed by Engle and Kroner (1995) <> has been used to estimate the bivariate time series data using Bayesian technique.

Version: 0.1.1
Imports: MTS, coda, mvtnorm
Published: 2022-12-05
DOI: 10.32614/CRAN.package.BayesBEKK
Author: Achal Lama, Girish K Jha, K N Singh and Bishal Gurung
Maintainer: Achal Lama <achal.lama at>
License: GPL-3
NeedsCompilation: no
CRAN checks: BayesBEKK results


Reference manual: BayesBEKK.pdf


Package source: BayesBEKK_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): BayesBEKK_0.1.1.tgz, r-oldrel (arm64): BayesBEKK_0.1.1.tgz, r-release (x86_64): BayesBEKK_0.1.1.tgz, r-oldrel (x86_64): BayesBEKK_0.1.1.tgz
Old sources: BayesBEKK archive


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