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robustbetareg
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]
[Scholar Profile | Author Map]
All associated links for this package
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 03 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
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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