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  • 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
  • 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.
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