Package: tseriesTARMA 0.5-2
Simone Giannerini
tseriesTARMA: Analysis of Nonlinear Time Series Through Threshold Autoregressive Moving Average Models (TARMA) Models
Routines for nonlinear time series analysis based on Threshold Autoregressive Moving Average (TARMA) models. It provides functions and methods for: TARMA model fitting and forecasting, including robust estimators, see Goracci et al. JBES (2025) <doi:10.1080/07350015.2024.2412011>; tests for threshold effects, see Giannerini et al. JoE (2024) <doi:10.1016/j.jeconom.2023.01.004>, Goracci et al. Statistica Sinica (2023) <doi:10.5705/ss.202021.0120>, Angelini et al. (2024) OBES <doi:10.1111/obes.12647>; unit-root tests based on TARMA models, see Chan et al. Statistica Sinica (2024) <doi:10.5705/ss.202022.0125>.
Authors:
tseriesTARMA_0.5-2.tar.gz
tseriesTARMA_0.5-2.zip(r-4.7-x86_64)tseriesTARMA_0.5-2.zip(r-4.7-arm64)tseriesTARMA_0.5-2.zip(r-4.6-x86_64)tseriesTARMA_0.5-2.zip(r-4.6-arm64)
tseriesTARMA_0.5-2.tar.gz(r-4.7-arm64)tseriesTARMA_0.5-2.tar.gz(r-4.7-x86_64)tseriesTARMA_0.5-2.tar.gz(r-4.6-arm64)tseriesTARMA_0.5-2.tar.gz(r-4.6-x86_64)
tseriesTARMA_0.5-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tseriesTARMA/json (API)
| # Install 'tseriesTARMA' in R: |
| install.packages('tseriesTARMA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b749cb5809. Checks:9 OK, 1 WARNING. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 171 | ||
| linux-devel-x86_64 | OK | 163 | ||
| source / vignettes | OK | 206 | ||
| linux-release-arm64 | OK | 123 | ||
| linux-release-x86_64 | OK | 153 | ||
| windows-devel-arm64 | OK | 228 | ||
| windows-devel-x86_64 | OK | 156 | ||
| windows-release-arm64 | WARNING | 241 | ||
| windows-release-x86_64 | OK | 122 | ||
| wasm-release | OK | 97 |
Exports:plot.tsfitTAR.testTAR.test.BTARMA.fitTARMA.fit2TARMA.simTARMA.testTARMAGARCH.testTARMAur.testTARMAur.test.B
Dependencies:chroncodetoolsdigestDistributionUtilsfitdistrplusFNNfracdifffuturefuture.applyGeneralizedHyperbolicglobalskernlabKernSmoothkslatticelbfgsb3clistenvMASSmathjaxrMatrixmclustmgcvmulticoolmvtnormnlmenloptrnumDerivparallellypracmarbibutilsRcppRcppArmadilloRdpackrlangRsolnprugarchSkewHyperbolicspdsurvivaltruncnormxtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Andrews Tabulated Critical Values | ACValues |
| Plot from fitted/forecasted time series models. | plot.tsfit |
| Forecast from fitted TARMA models. | predict.TARMA |
| Methods for TARMA fits | coef.TARMA print.TARMA residuals.TARMA vcov.TARMA |
| Methods for TARMA tests | print.TARMAtest |
| Tabulated Critical Values for the Unit Root IMA vs TARMA test | supLMQur |
| AR versus TARMA supLM robust test for nonlinearity | TAR.test |
| AR versus TAR bootstrap supLM test for nonlinearity | TAR.test.B |
| TARMA Modelling of Time Series | TARMA.fit |
| TARMA Modelling of Time Series | TARMA.fit2 |
| Simulation of a two-regime 'TARMA(p1,p2,q1,q2)' process | TARMA.sim |
| ARMA versus TARMA (and AR versus TAR) supLM tests for nonlinearity | TARMA.test |
| ARMA GARCH versus TARMA GARCH supLM test for nonlinearity | TARMAGARCH.test |
| Unit root supLM test for an integrated MA versus a stationary TARMA process | TARMAur.test |
| Unit root supLM test for an integrated MA versus a stationary TARMA process | TARMAur.test.B |