Publisher:
Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, London
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives...
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ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
Signature:
DS 243 (2017,29)
Inter-library loan:
No inter-library loan
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on 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 indices for the same functions using analytical and resampling methods. This paper serves as an introduction to the package and displays basic functionality of the functions contained within.
