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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: | 0.1.2 |
| Imports: | methods, stats, utils, graphics, Formula, grDevices, GIGrvg, coda |
| Published: | 2024-07-22 |
| 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/mtar/issues |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | no |
| In views: | TimeSeries |
| CRAN checks: | mtarm results |
| Reference manual: | mtarm.pdf |
| Package source: | mtarm_0.1.2.tar.gz |
| Windows binaries: | r-devel: mtarm_0.1.2.zip, r-release: mtarm_0.1.2.zip, r-oldrel: mtarm_0.1.2.zip |
| macOS binaries: | r-release (arm64): mtarm_0.1.2.tgz, r-oldrel (arm64): mtarm_0.1.2.tgz, r-release (x86_64): mtarm_0.1.2.tgz, r-oldrel (x86_64): mtarm_0.1.2.tgz |
| Old sources: | mtarm archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.