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Semiparametric Regression Functionals

 

作者: Michael Leblanc,   John Crowley,  

 

期刊: Journal of the American Statistical Association  （Taylor Available online 1995）
卷期: Volume 90, issue 429  

页码: 95-105

 

ISSN:0162-1459

 

年代: 1995

 

DOI:10.1080/01621459.1995.10476492

 

出版商: Taylor & Francis Group

 

关键词: Empirical likelihood;Generalized linear model;Nonparametric likelihood

 

数据来源: Taylor

 

摘要:

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.

 

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