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Article: Statistical inference for induced L-statistics: a random perturbation approach

TitleStatistical inference for induced L-statistics: a random perturbation approach
Authors
KeywordsOrder Statistics
Random Perturbation
L-Statistics
Issue Date2009
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10485252.asp
Citation
Journal of Nonparametric Statistics, 2009, v. 21, p. 863-876 How to Cite?
AbstractSuppose that X and Y are two numerical characteristics defined for each individual in a population. In a random sample of (X,Y) with sample size n, denote the rth ordered X variate by Xr:n and the associated Y variate, the induced rth order statistics, by Y[r:n], respectively. Induced order statistics arise naturally in the context of selection where individuals ought to be selected by their ranks in a related X value due to difficulty or h∑gh costs of obtaining Y at the time of selection. The induced L-statistics, which take the form of, are very useful in regression analysis, especially when the observations are subject to a type-II censoring scheme with respect to the dependent variable, or when the regression function at a given quantile of the predictor variable is of interest. The limiting variance of the induced L-statistics involve the underlying regression function and inferences based on nonparametric estimation are often unstable. In this paper, we consider the distributional approximation of the induced L-statistics by the random perturbation method. Large sample properties of the randomly perturbed induced L-statistics are established. Numerical studies are also conducted to illustrate the method and to assess its finite-sample performance. © 2009 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/221688
ISSN
2015 Impact Factor: 0.446
2015 SCImago Journal Rankings: 0.980
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, J-
dc.contributor.authorZhao, L-
dc.contributor.authorLeng, C-
dc.date.accessioned2015-12-04T15:29:07Z-
dc.date.available2015-12-04T15:29:07Z-
dc.date.issued2009-
dc.identifier.citationJournal of Nonparametric Statistics, 2009, v. 21, p. 863-876-
dc.identifier.issn1048-5252-
dc.identifier.urihttp://hdl.handle.net/10722/221688-
dc.description.abstractSuppose that X and Y are two numerical characteristics defined for each individual in a population. In a random sample of (X,Y) with sample size n, denote the rth ordered X variate by Xr:n and the associated Y variate, the induced rth order statistics, by Y[r:n], respectively. Induced order statistics arise naturally in the context of selection where individuals ought to be selected by their ranks in a related X value due to difficulty or h∑gh costs of obtaining Y at the time of selection. The induced L-statistics, which take the form of, are very useful in regression analysis, especially when the observations are subject to a type-II censoring scheme with respect to the dependent variable, or when the regression function at a given quantile of the predictor variable is of interest. The limiting variance of the induced L-statistics involve the underlying regression function and inferences based on nonparametric estimation are often unstable. In this paper, we consider the distributional approximation of the induced L-statistics by the random perturbation method. Large sample properties of the randomly perturbed induced L-statistics are established. Numerical studies are also conducted to illustrate the method and to assess its finite-sample performance. © 2009 Taylor & Francis.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/10485252.asp-
dc.relation.ispartofJournal of Nonparametric Statistics-
dc.subjectOrder Statistics-
dc.subjectRandom Perturbation-
dc.subjectL-Statistics-
dc.titleStatistical inference for induced L-statistics: a random perturbation approach-
dc.typeArticle-
dc.identifier.emailXu, J: xujf@hku.hk-
dc.identifier.authorityXu, J=rp02086-
dc.identifier.doi10.1080/10485250902980584-
dc.identifier.scopuseid_2-s2.0-70449382225-
dc.identifier.volume21-
dc.identifier.spage863-
dc.identifier.epage876-
dc.identifier.isiWOS:000271475100009-

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