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: 0.1.0
Depends: R (≥ 3.3.0), MTS, coda, mvtnorm
Published: 2019-10-11
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

Downloads:

Reference manual: BayesBEKK.pdf
Package source: BayesBEKK_0.1.0.tar.gz
Windows binaries: r-devel: BayesBEKK_0.1.0.zip, r-devel-gcc8: BayesBEKK_0.1.0.zip, r-release: BayesBEKK_0.1.0.zip, r-oldrel: BayesBEKK_0.1.0.zip
OS X binaries: r-release: BayesBEKK_0.1.0.tgz, r-oldrel: BayesBEKK_0.1.0.tgz

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