This package is considered a duplicate. The official version of this package is found at:https://cran.r-universe.dev/BayesBEKK

Package: BayesBEKK 0.1.1

Achal Lama

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.

Authors:Achal Lama, Girish K Jha, K N Singh and Bishal Gurung

BayesBEKK_0.1.1.tar.gz
BayesBEKK_0.1.1.zip(r-4.7)BayesBEKK_0.1.1.zip(r-4.6)BayesBEKK_0.1.1.zip(r-4.5)
BayesBEKK_0.1.1.tgz(r-4.6-any)BayesBEKK_0.1.1.tgz(r-4.5-any)
BayesBEKK_0.1.1.tar.gz(r-4.7-any)BayesBEKK_0.1.1.tar.gz(r-4.6-any)
BayesBEKK_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesBEKK/json (API)

# Install 'BayesBEKK' in R:

install.packages('BayesBEKK', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

On CRAN:

archived packages r-universe

1.70 score 5 stars 228 downloads 1 exports 20 dependencies

Last updated from:72c2671407 (on package/BayesBEKK). Checks:9 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	128
source / vignettes	OK	161
linux-release-x86_64	OK	112
macos-release-arm64	OK	131
macos-oldrel-arm64	OK	80
windows-devel	OK	101
windows-release	OK	104
windows-oldrel	OK	101
wasm-release	OK	92