qrcmNP: Nonlinear and Penalized Quantile Regression Coefficients
Modeling
Penalized and nonlinear parametric modeling of quantile
regression coefficient functions. The penalized integrated loss
minimization estimator (lasso and group lasso penalties) of Sottile,
Frumento, Chiodi and Bottai (2020) <doi:10.1177/1471082X19825523>
performs covariate selection using the information on all quantiles
simultaneously. Nonlinear parametric quantile models, in which the
conditional quantile function can be a nonlinear function of the
parameters, of the covariates or both, are estimated by integrated
loss minimization as in Bottai and Cilluffo (2020)
<doi:10.1177/0962280220941159>. Both approaches extend the quantile
regression coefficients modeling framework of Frumento and Bottai
(2016) <doi:10.1111/biom.12410> implemented in 'qrcm'.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
graphics, grDevices, qrcm (≥ 3.0), stats, survival (≥ 2.41), utils |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-10-30 |
| DOI: |
10.32614/CRAN.package.qrcmNP |
| Author: |
Gianluca Sottile 
[aut, cre],
Paolo Frumento [aut, cph] (author of parts of the code adapted from
'qrcm') |
| Maintainer: |
Gianluca Sottile <gianluca.sottile at unipa.it> |
| BugReports: |
https://github.com/gianluca-sottile/qrcmNP/issues |
| License: |
GPL-2 |
| URL: |
https://github.com/gianluca-sottile/qrcmNP |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
qrcmNP citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
qrcmNP results |
Documentation:
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