Power Logit Regression for Modeling Bounded Data R package PLreg version 0.4.1 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) <arXiv:2202.01697>. Software Depends: R (>= 2.10) Imports: BBmisc, EnvStats, Formula, gamlss.dist, GeneralizedHyperbolic, methods, nleqslv, stats, VGAM, zipfR Suggests: rmarkdown, knitr, testthat (>= 3.0.0) Felipe Queiroz <ffelipeq@outlook.com> Comprehensive R Archive Network (CRAN) Felipe Queiroz [aut, cre], Silvia Ferrari [aut] GPL (>= 3) 2023-02-16 application/tgz https://CRAN.R-project.org/package=PLreg doi:10.32614/CRAN.package.PLreg