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) <http://www.jstor.org/stable/3532933> 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 icar.gov.in>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	BayesBEKK results

Documentation:

Reference manual:

BayesBEKK.pdf

Downloads:

Package source:	BayesBEKK_0.1.1.tar.gz
Windows binaries:	r-devel: BayesBEKK_0.1.1.zip, r-release: BayesBEKK_0.1.1.zip, r-oldrel: BayesBEKK_0.1.1.zip
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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