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.tar.gz(r-4.5-noble)BayesBEKK_0.1.1.tar.gz(r-4.4-noble)
BayesBEKK_0.1.1.tgz(r-4.4-emscripten)BayesBEKK_0.1.1.tgz(r-4.3-emscripten)
BayesBEKK.pdf |BayesBEKK.html
BayesBEKK/json (API)

# Install 'BayesBEKK' in R:
install.packages('BayesBEKK', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1 exports 0.00 score 20 dependencies 317 downloads

Last updated 2 years agofrom:d6c40db9b9. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 01 2024
R-4.5-linuxOKSep 01 2024

Exports:BayesianBEKK

Dependencies:codacvarfastICAfBasicsfGarchgbutilsgsslatticeMASSMatrixMTSmvtnormrbibutilsRcppRcppEigenRdpackspatialstabledisttimeDatetimeSeries