Package: PTSR 0.1.2
PTSR: Positive Time Series Regression
A collection of functions to simulate, estimate and forecast a wide range of regression based dynamic models for positive time series. This package implements the results presented in Prass, T.S.; Carlos, J.H.; Taufemback, C.G. and Pumi, G. (2022). "Positive Time Series Regression" <arxiv:2201.03667>.
Authors:
PTSR_0.1.2.tar.gz
PTSR_0.1.2.zip(r-4.5)PTSR_0.1.2.zip(r-4.4)PTSR_0.1.2.zip(r-4.3)
PTSR_0.1.2.tgz(r-4.4-any)PTSR_0.1.2.tgz(r-4.3-any)
PTSR_0.1.2.tar.gz(r-4.5-noble)PTSR_0.1.2.tar.gz(r-4.4-noble)
PTSR_0.1.2.tgz(r-4.4-emscripten)PTSR_0.1.2.tgz(r-4.3-emscripten)
PTSR.pdf |PTSR.html✨
PTSR/json (API)
NEWS
| # Install 'PTSR' in R: |
| install.packages('PTSR', repos = c('https://tsprass.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 3 years agofrom:a1ea830dc7. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 21 2024 |
| R-4.5-win | NOTE | Nov 21 2024 |
| R-4.5-linux | NOTE | Nov 21 2024 |
| R-4.4-win | OK | Nov 21 2024 |
| R-4.4-mac | OK | Nov 21 2024 |
| R-4.3-win | OK | Nov 21 2024 |
| R-4.3-mac | OK | Nov 21 2024 |
Exports:d.betapd.chid.Fd.gammad.invGaussd.logLogisd.logNormd.rayptsr.fitptsr.linkptsr.simr.betapr.chir.Fr.gammar.invGaussr.logLogisr.logNormr.ray
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Reparametrized Distributions | d.betap d.chi d.F d.gamma d.invGauss d.logLogis d.logNorm d.ray ddist r.betap r.chi r.F r.gamma r.invGauss r.logLogis r.logNorm r.ray rdist |
| Predict method for PTSR | predict.ptsr |
| Print Method of class PTSR | print.ptsr |
| Title Function to fit a PTSR model | ptsr.fit |
| Create a Link for PTSR models | ptsr.link |
| Function to simulate a PTSR model | ptsr.sim |
| Summary Method of class PTSR | print.summary.ptsr summary summary.ptsr |
