Package: PLreg 0.4.0

PLreg: Power Logit Regression for Modeling Bounded Data

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>.

Authors:Felipe Queiroz [aut, cre], Silvia Ferrari [aut]

PLreg_0.4.0.tar.gz
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PLreg.pdf |PLreg.html
PLreg/json (API)
NEWS

# Install 'PLreg' in R:
install.packages('PLreg', repos = c('https://ffqueiroz.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ffqueiroz/plreg/issues

Datasets:

On CRAN:

11 exports 0.64 score 41 dependencies 2 scripts 281 downloads

Last updated 2 years agofrom:78cb146d92. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 11 2024
R-4.5-winOKSep 11 2024
R-4.5-linuxOKSep 11 2024
R-4.4-winOKSep 11 2024
R-4.4-macOKSep 11 2024
R-4.3-winOKSep 11 2024
R-4.3-macOKSep 11 2024

Exports:CI.lambdadPLenvelopeextra.parameterinfluencePLregPLreg.controlpPLqPLrPLsandwich

Dependencies:backportsBBmisccheckmateclicolorspacedata.tableDistributionUtilsEnvStatsfansifarverFormulagamlss.distGeneralizedHyperbolicggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnleqslvnlmenortestpillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsVGAMviridisLitewithrzipfR