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TAR: Bayesian Modeling of Autoregressive Threshold Time Series Models

Identification and estimation of the autoregressive threshold models with Gaussian noise, as well as positive-valued time series. The package provides the identification of the number of regimes, the thresholds and the autoregressive orders, as well as the estimation of remain parameters. The package implements the methodology from the 2005 paper: Modeling Bivariate Threshold Autoregressive Processes in the Presence of Missing Data <doi:10.1081/STA-200054435>.

Version: 1.0
Depends: mvtnorm
Published: 2017-02-24
Author: Hanwen Zhang, Fabio H. Nieto
Maintainer: Hanwen Zhang <hanwengutierrez at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: TAR results

Documentation:

Reference manual: TAR.pdf

Downloads:

Package source: TAR_1.0.tar.gz
Windows binaries: r-devel: TAR_1.0.zip, r-release: TAR_1.0.zip, r-oldrel: TAR_1.0.zip
macOS binaries: r-release (arm64): TAR_1.0.tgz, r-oldrel (arm64): TAR_1.0.tgz, r-release (x86_64): TAR_1.0.tgz, r-oldrel (x86_64): TAR_1.0.tgz

Linking:

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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.