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("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},
#> }
The unitquantreg
package is released under the Apache License, Version
2.0. Please, see file
LICENSE.md
.