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robustbetareg  

Robust Beta Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("robustbetareg", "0.3.0")



Attach the package and use:
library("robustbetareg")
Maintained by
Felipe Queiroz
[Scholar Profile | Author Map]
First Published: 2022-10-28
Latest Update: 2022-10-28
Description:
Robust estimators for the beta regression, useful for modeling bounded continuous data. Currently, four types of robust estimators are supported. They depend on a tuning constant which may be fixed or selected by a data-driven algorithm also implemented in the package. Diagnostic tools associated with the fitted model, such as the residuals and goodness-of-fit statistics, are implemented. Robust Wald-type tests are available. More details about robust beta regression are described in Maluf et al. (2022) .
How to cite:
Felipe Queiroz (2022). robustbetareg: Robust Beta Regression. R package version 0.3.0, https://cran.r-project.org/web/packages/robustbetareg. Accessed 16 Mar. 2025.
Previous versions and publish date:
No previous versions
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View robustbetareg citation profile
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Complete documentation for robustbetareg
Functions, R codes and Examples using the robustbetareg R package
Some associated functions: EGB . Firm . HIC . methodsrobustbetareg . plot.robustbetareg . plotenvelope . predict . residuals.robustbetareg . robustbetareg.control . robustbetareg . set.link . waldtypetest . 
Some associated R codes: Aux-Functions.R . Firm.R . HIC.R . Show-Result.R . robustbetareg.R .  Full robustbetareg package functions and examples
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