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unitquantreg: Parametric Quantile Regression Models for Bounded Data

A collection of parametric quantile regression models for bounded data. At present, the package provides 13 parametric quantile regression models. It can specify regression structure for any quantile and shape parameters. It also provides several S3 methods to extract information from fitted model, such as residual analysis, prediction, plotting, and model comparison. For more computation efficient the [dpqr]'s, likelihood, score and hessian functions are written in C++. For further details see Mazucheli et. al (2022) <doi:10.1016/j.cmpb.2022.106816>.

Version: 0.0.6
Depends: R (≥ 3.5.0)
Imports: Rcpp, optimx, stats, quantreg, Formula, MASS, numDeriv
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0), rmarkdown, knitr, lmtest, ggplot2, covr
Published: 2023-09-06
DOI: 10.32614/CRAN.package.unitquantreg
Author: André F. B. Menezes ORCID iD [aut, cre], Josmar Mazucheli ORCID iD [aut]
Maintainer: André F. B. Menezes <andrefelipemaringa at gmail.com>
BugReports: https://github.com/AndrMenezes/unitquantreg/issues
License: Apache License (≥ 2)
URL: https://andrmenezes.github.io/unitquantreg/
NeedsCompilation: yes
Citation: unitquantreg citation info
Materials: README NEWS
CRAN checks: unitquantreg results

Documentation:

Reference manual: unitquantreg.pdf
Vignettes: Structure and functionality
Get started

Downloads:

Package source: unitquantreg_0.0.6.tar.gz
Windows binaries: r-devel: unitquantreg_0.0.6.zip, r-release: unitquantreg_0.0.6.zip, r-oldrel: unitquantreg_0.0.6.zip
macOS binaries: r-release (arm64): unitquantreg_0.0.6.tgz, r-oldrel (arm64): unitquantreg_0.0.6.tgz, r-release (x86_64): unitquantreg_0.0.6.tgz, r-oldrel (x86_64): unitquantreg_0.0.6.tgz
Old sources: unitquantreg archive

Linking:

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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.