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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) <doi:10.48550/arXiv.2209.11315>.
Version: | 0.3.0 |
Depends: | R (≥ 3.5.0), betareg |
Imports: | Rmpfr, rstudioapi, crayon, pracma, numDeriv, Formula, robustbase, zoo, methods, graphics, BBmisc, MASS, miscTools, Matrix |
Suggests: | covr, testthat (≥ 3.0.0) |
Published: | 2022-10-28 |
DOI: | 10.32614/CRAN.package.robustbetareg |
Author: | Felipe Queiroz [aut, cre], Yuri Maluf [aut], Silvia Ferrari [ctb] |
Maintainer: | Felipe Queiroz <ffelipeq at outlook.com> |
License: | GPL-3 |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | robustbetareg results |
Reference manual: | robustbetareg.pdf |
Package source: | robustbetareg_0.3.0.tar.gz |
Windows binaries: | r-devel: robustbetareg_0.3.0.zip, r-release: robustbetareg_0.3.0.zip, r-oldrel: robustbetareg_0.3.0.zip |
macOS binaries: | r-release (arm64): robustbetareg_0.3.0.tgz, r-oldrel (arm64): robustbetareg_0.3.0.tgz, r-release (x86_64): robustbetareg_0.3.0.tgz, r-oldrel (x86_64): robustbetareg_0.3.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.