Semiparametric Regression Functionals

descriptionPublicationkeyboard_double_arrow_right Article 01 Mar 1995Publisher:JSTORJournal:Journal of the American Statistical Association, volume 90, page 95 (issn: 0162-1459,

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Authors: Michael Leblanc; John Crowley;

doi: 10.2307/2291133 , 10.1080/01621459.1995.10476492

Semiparametric Regression Functionals

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Abstract

Abstract A regression method is developed for a general class of functionals. A semiparametric linear model is adopted, and the regression parameters are estimated by maximizing a profiled nonparametric or empirical likelihood based on a local estimate of the conditional distribution function. Simulated and real data examples are shown, including an application of quantile regression to censored survival data from a clinical trial for myeloma.

Related Organizations

University of Toronto
Canada
Fred Hutchinson Cancer Research Center
South Africa
Fred Hutchinson Cancer Research Center
United States

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