文章基本信息

标题：Isotonic Quantile Regression: Asymptotics and Bootstrap
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作者：Jason Abrevaya ; Purdue University ; W.\ Lafayette, IN, USA 等
期刊名称：Sankhya. Series A, mathematical statistics and probability
印刷版ISSN：0976-836X
电子版ISSN：0976-8378
出版年度：2005
卷号：67
期号：02
出版社：Indian Statistical Institute
摘要：This paper considers a nonparametric model in which (i)~the conditional quantile function is assumed to be nondecreasing and (ii)~the distribution of the error disturbance may depend upon the covariate. For this general model, the (pointwise) limiting distribution of the isotonic quantile regression estimator (Casady and Cryer~(1976)) is derived. Since the bootstrap is not consistent for this estimator, an adjusted version of the bootstrap is discussed as an alternative method for inference. An empirical application to birthweights is considered.
关键词：Isotonic quantile regression, cube-root asymptotics, bootstrap