Additive Models for Quantile Regression

Additive Models for Quantile Regression: Model Selection and Confidence Bandaids

We describe some recent development of nonparametric methods for estimating conditional quantile functions using additive models with total variation roughness penalties. We focus attention primarily on selection of smoothing parameters and on the construction of confidence bands for the nonparametric components. Both pointwise and uniform confidence bands are introduced; the uniform bands are based on the Hotelling (1939) tube approach. Some simulation evidence is presented to evaluate finite sample performance and the methods are also illustrated with an application to modeling childhood malnutrition in India. The methods described have been implemented in the R package {\tt quantreg}.



The paper is available in pdf. Some notes on Hotelling tubes are also available here. R code for the simulations reported in the paper are available here. as a gzipped tar archive.




Comments are, of course, always welcome.