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Power logit regression models for bounded continuous data, in which the density generator may be normal, Student-t, power exponential, slash, hyperbolic, sinh-normal, or type II logistic. Diagnostic tools associated with the fitted model, such as the residuals, local influence measures, leverage measures, and goodness-of-fit statistics, are implemented. The estimation process follows the maximum likelihood approach and, currently, the package supports two types of estimators: the usual maximum likelihood estimator and the penalized maximum likelihood estimator. More details about power logit regression models are described in Queiroz and Ferrari (2022) <doi:10.48550/arXiv.2202.01697>.
| Version: | 0.4.1 |
| Depends: | R (≥ 2.10) |
| Imports: | BBmisc, EnvStats, Formula, gamlss.dist, GeneralizedHyperbolic, methods, nleqslv, stats, VGAM, zipfR |
| Suggests: | rmarkdown, knitr, testthat (≥ 3.0.0) |
| Published: | 2023-02-16 |
| Author: | Felipe Queiroz [aut, cre], Silvia Ferrari [aut] |
| Maintainer: | Felipe Queiroz <ffelipeq at outlook.com> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/ffqueiroz/PLreg |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | PLreg results |
| Reference manual: | PLreg.pdf |
| Package source: | PLreg_0.4.1.tar.gz |
| Windows binaries: | r-devel: PLreg_0.4.1.zip, r-release: PLreg_0.4.1.zip, r-oldrel: PLreg_0.4.1.zip |
| macOS binaries: | r-release (arm64): PLreg_0.4.1.tgz, r-oldrel (arm64): PLreg_0.4.1.tgz, r-release (x86_64): PLreg_0.4.1.tgz, r-oldrel (x86_64): PLreg_0.4.1.tgz |
| Old sources: | PLreg archive |
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