Positive Time Series Regression
Overview
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.; Pumi, G.; Taufemback, C.G. and Carlos, J.H. (2025). "Positive time series regression models: theoretical and computational aspects". Computational Statistics 40, 1185–1215. doi:10.1007/s00180-024-01531-z.
- Fixed the description file: NeedsCompilation is now set to "no".
- Updated the reference to the main article.
- Fixed the ptsr.link function. Now both derivatives corresponding to the identity link return a vector of ones with the same size of the function's argument.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 7
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 50%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing PTSR adds 7 packages (6 with compiled code, 4.2 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppArmadillo 1.0 MB, actuar 971 KB.
Code & Tests
People & History
Package metadata
- First published
- 2022-01-13
- Total releases
- 4 / 4 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.0.0
- Download size
- 14 KB
Cite
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Run in R for the authors' preferred citation:
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