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 DOI: 10.32614/CRAN.package.PLreg 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=PLreg to link to this page.
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