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PLreg  

Power Logit Regression for Modeling Bounded Data
View on CRAN: Click here


Download and install PLreg package within the R console
Install from CRAN:
install.packages("PLreg")

Install from Github:
library("remotes")
install_github("cran/PLreg")

Install by package version:
library("remotes")
install_version("PLreg", "0.4.1")



Attach the package and use:
library("PLreg")
Maintained by
Felipe Queiroz
[Scholar Profile | Author Map]
First Published: 2022-03-30
Latest Update: 2023-02-16
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) .
How to cite:
Felipe Queiroz (2022). PLreg: Power Logit Regression for Modeling Bounded Data. R package version 0.4.1, https://cran.r-project.org/web/packages/PLreg. Accessed 01 May. 2025.
Previous versions and publish date:
0.2.0 (2022-03-30 09:20), 0.3.0 (2022-12-19 20:10), 0.3.1 (2023-01-23 23:00), 0.4.0 (2023-02-11 23:40)
Other packages that cited PLreg R package
View PLreg citation profile
Other R packages that PLreg depends, imports, suggests or enhances
Complete documentation for PLreg
Functions, R codes and Examples using the PLreg R package
Some associated functions: Firm . PL . PLreg . PLregcontrol . PeruVotes . bodyfat_Aeolus . envelope . extra.parameter . influence . methodsPLreg . plot.PLreg . residuals.PLreg . sandwich . 
Some associated R codes: Firm.R . PLdist.R . PLreg.R . PeruVotes.R . bodyfat_Aeolus.R .  Full PLreg package functions and examples
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