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  • 标题:Asymptotic Efficiency of Maximum Likelihood Estimators Under Misspecified Models
  • 本地全文:下载
  • 作者:Malay Ghosh ; Jihyun Song
  • 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:537-542
  • DOI:10.1234/pjsor.v8i3.525
  • 语种:English
  • 出版社:College of Statistical and Actuarial Sciences
  • 摘要: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";} We illustrate with examples when and how maximum likelihood estimators continue to be asymptotically efficient even under misspecified models. Also, we provide a necessary and sufficient condition under which a subset of the vector of MLE's retains its asymptotic efficiency under misspecified models even though the MLE itself is not fully asymptotic efficient.
  • 关键词:Asymptotic, Maximum Likelihood, Misspecified Models
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