mtarm: Bayesian Estimation of Multivariate Threshold Autoregressive Models

Estimation, inference and forecasting using the Bayesian approach for multivariate threshold autoregressive (TAR) models in which the distribution used to describe the noise process belongs to the class of Gaussian variance mixtures.

Version: 0.1.9
Imports: methods, stats, utils, graphics, Formula, grDevices, GIGrvg, coda, mvtnorm, future.apply, progressr, future
Suggests: cli, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-06-12
DOI: 10.32614/CRAN.package.mtarm
Author: Luis Hernando Vanegas [aut, cre], Sergio Alejandro Calderón [aut], Luz Marina Rondón [aut]
Maintainer: Luis Hernando Vanegas <lhvanegasp at unal.edu.co>
BugReports: https://github.com/lhvanegasp/mtarm/issues
License: GPL-2 | GPL-3
URL: https://lhvanegasp.github.io/mtarm/
NeedsCompilation: no
Materials: README
In views: TimeSeries
CRAN checks: mtarm results

Documentation:

Reference manual: mtarm.html , mtarm.pdf
Vignettes: Introduction to the mtarm Package (source, R code)

Downloads:

Package source: mtarm_0.1.9.tar.gz
Windows binaries: r-devel: mtarm_0.1.8.zip, r-release: mtarm_0.1.8.zip, r-oldrel: mtarm_0.1.8.zip
macOS binaries: r-release (arm64): mtarm_0.1.8.tgz, r-oldrel (arm64): mtarm_0.1.8.tgz, r-release (x86_64): mtarm_0.1.8.tgz, r-oldrel (x86_64): mtarm_0.1.8.tgz
Old sources: mtarm archive

Linking:

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