Package: TAR 1.0

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>.

Authors:Hanwen Zhang, Fabio H. Nieto

TAR_1.0.tar.gz
TAR_1.0.zip(r-4.7-any)TAR_1.0.zip(r-4.6-any)TAR_1.0.zip(r-4.5-any)
TAR_1.0.tgz(r-4.6-any)TAR_1.0.tgz(r-4.5-any)
TAR_1.0.tar.gz(r-4.7-any)TAR_1.0.tar.gz(r-4.6-any)
TAR_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
TAR/json (API)

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

On CRAN:

Conda:

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

2.68 score 3 stars 16 scripts 357 downloads 12 mentions 10 exports 1 dependencies

Last updated from:0b89afdf66. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK85
source / vignettesOK148
linux-releaseOK87
macos-releaseOK141
macos-oldrelOK214
windows-develOK62
windows-releaseOK71
windows-oldrelOK66
wasm-releaseOK81

Exports:ARorder.lognormARorder.normLS.lognormLS.normParam.lognormParam.normreg.thr.lognormreg.thr.normsimu.tar.lognormsimu.tar.norm

Dependencies:mvtnorm