bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

Tools to research Bayesian Vector heterogeneous autoregressive (VHAR) model, referring to Kim & Baek (2023) (<doi:10.1080/00949655.2023.2281644>). 'bvhar' can model Vector Autoregressive (VAR), VHAR, Bayesian VAR (BVAR), and Bayesian VHAR (BVHAR) models.

Version: 2.0.1
Depends: R (≥ 3.6.0)
Imports: lifecycle, magrittr, Rcpp, ggplot2, tidyr, tibble, dplyr, foreach, purrr, stats, optimParallel, posterior, bayesplot
LinkingTo: BH, Rcpp, RcppEigen (≥ 0.3.4.0.0)
Suggests: covr, knitr, parallel, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-03-01
Author: Young Geun Kim ORCID iD [aut, cre, cph], Changryong Baek [ctb]
Maintainer: Young Geun Kim <ygeunkimstat at gmail.com>
BugReports: https://github.com/ygeunkim/bvhar/issues
License: GPL (≥ 3)
URL: https://ygeunkim.github.io/package/bvhar/, https://github.com/ygeunkim/bvhar
NeedsCompilation: yes
Citation: bvhar citation info
Materials: README NEWS
CRAN checks: bvhar results

Documentation:

Reference manual: bvhar.pdf
Vignettes: Introduction to bvhar
Empirical Bayes
Forecasting
Cpp source usage
Minnesota Prior
Shrinkage Priors

Downloads:

Package source: bvhar_2.0.1.tar.gz
Windows binaries: r-devel: bvhar_2.0.1.zip, r-release: bvhar_2.0.1.zip, r-oldrel: bvhar_2.0.1.zip
macOS binaries: r-release (arm64): bvhar_2.0.0.tgz, r-oldrel (arm64): bvhar_2.0.0.tgz, r-release (x86_64): bvhar_2.0.1.tgz
Old sources: bvhar archive

Linking:

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