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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.

Versions across snapshots

VersionRepositoryFileSize
0.1.1 rolling linux/jammy R-4.5 BayesBEKK_0.1.1.tar.gz 16.3 KiB
0.1.1 rolling linux/noble R-4.5 BayesBEKK_0.1.1.tar.gz 16.2 KiB
0.1.1 rolling source/ R- BayesBEKK_0.1.1.tar.gz 2.7 KiB
0.1.1 latest linux/jammy R-4.5 BayesBEKK_0.1.1.tar.gz 16.3 KiB
0.1.1 latest linux/noble R-4.5 BayesBEKK_0.1.1.tar.gz 16.2 KiB
0.1.1 latest source/ R- BayesBEKK_0.1.1.tar.gz 2.7 KiB
0.1.1 2026-04-26 source/ R- BayesBEKK_0.1.1.tar.gz 2.7 KiB
0.1.1 2026-04-23 source/ R- BayesBEKK_0.1.1.tar.gz 2.7 KiB
0.1.1 2026-04-09 windows/windows R-4.5 BayesBEKK_0.1.1.zip 19.1 KiB
0.1.1 2025-04-20 source/ R- BayesBEKK_0.1.1.tar.gz 2.7 KiB

Dependencies (latest)

Imports