文章基本信息

标题：On the Consistency of a Class of Nonlinear Regression Estimators
本地全文：下载
作者：Asheber Abebe ; Joseph W. McKean ; Huybrechts F. Bindele 等
期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2012
卷号：8
期号：3
页码：543-555
DOI：10.1234/pjsor.v8i3.526
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} In this paper, we study conditions sufficient for strong consistency of a class of estimators of parameters of nonlinear regression models. The study considers continuous functions depending on a vector of parameters and a set of random regressors. The estimators chosen are minimizers of a generalized form of the signed-rank norm. The generalization allows us to make consistency statements about minimizers of a wide variety of norms including the L1 and L2 norms. By implementing trimming, it is shown that high breakdown estimates can be obtained based on the proposed dispersion function.
关键词：Nonlinear regression, Signed-rank, Order statistics, Strong consistency.