Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/64734
Authors: 
Koenker, Roger
Year of Publication: 
2010
Series/Report no.: 
cemmap working paper CWP33/10
Abstract: 
Additive models for conditional quantile functions provide an attractive framework for nonparametric regression applications focused on features of the response beyond its central tendency. Total variation roughness penalities can be used to control the smoothness of the additive components much as squared Sobelev penalties are used for classical L2 smoothing splines. We describe a general approach to estimation and inference for additive models of this type. 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.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
865.52 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.