Nonparametric Series Quantile Regression in R: A Vignette∗

Belloni, Chernozhukov, and Fernández-Val (2011) developed nonparametric quantile regression methods to estimate and make inference on conditional quantile models. The R package quantreg.nonpar implements these methods for partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. It also provides pointwise and uniform confidence intervals over a region of covariate values and/or quantile indexes for the same functions using analytical and resampling methods. This vignette serves as an introduction to the package and displays basic functionality of the functions contained within.