Package: PLreg
Title: Power Logit Regression for Modeling Bounded Data
Version: 0.4.1
Authors@R: c(
  person("Felipe", "Queiroz", email = "ffelipeq@outlook.com", role = c("aut", "cre")),
  person("Silvia", "Ferrari", email = "silviaferrari@usp.br", role = "aut"))
Description: 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>.
URL: https://github.com/ffqueiroz/PLreg
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
Imports: BBmisc, EnvStats, Formula, gamlss.dist, GeneralizedHyperbolic,
        methods, nleqslv, stats, VGAM, zipfR
Suggests: rmarkdown, knitr, testthat (>= 3.0.0)
Config/testthat/edition: 3
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2023-02-14 17:23:26 UTC; franc
Author: Felipe Queiroz [aut, cre],
  Silvia Ferrari [aut]
Maintainer: Felipe Queiroz <ffelipeq@outlook.com>
Repository: CRAN
Date/Publication: 2023-02-16 08:20:07 UTC
Built: R 4.6.0; ; 2026-04-26 09:29:24 UTC; unix
