The goal of unitquantreg is to provide tools for estimation and
inference on parametric quantile regression models for bounded data.
We developed routines with similar interface as stats::glm function,
which contains estimation, inference, residual analysis, prediction, and
model comparison.
For more computation efficient the [dpqr]’s, likelihood, score and
hessian functions are vectorized and written in C++.
You can install the stable version from CRAN with:
install.packages("unitquantreg")Or you can install the development version from GitHub with:
if(!require(remotes)) install.packages('remotes') remotes::install_github("AndrMenezes/unitquantreg", build_vignettes = TRUE)
You can then load the package
library(unitquantreg)and look at user manuals typing:
vignette("unitquantreg") vignette("structure_functionality")
Citation
citation("unitquantreg") #> #> To cite unitquantreg in publications use: #> #> Menezes A, Mazucheli J (2021). _unitquantreg: Parametric quantile #> regression models for bounded data_. R package version 0.0.3, #> <https://andrmenezes.github.io/unitquantreg/>. #> #> A BibTeX entry for LaTeX users is #> #> @Manual{, #> title = {unitquantreg: {P}arametric quantile regression models for bounded data}, #> author = {Andr{'}e F. B. Menezes and Josmar Mazucheli}, #> note = {R package version 0.0.3}, #> url = {https://andrmenezes.github.io/unitquantreg/}, #> year = {2021}, #> }
License
The unitquantreg package is released under the Apache License, Version
2.0. Please, see file
LICENSE.md.