Package: qrcmNP 1.0.0

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'.

Authors:Gianluca Sottile [aut, cre], Paolo Frumento [aut, cph]