Iterative weighted least-squares estimates in a heteroscedastic linear regression model

研究成果: Article

3 被引用数 (Scopus)

抄録

The aim of this study is to improve the e0ciency of weighted least-squares estimates for a regression parameter. An iterative procedure, starting with an unbiased estimate other than the unweighted least-squares estimate, yields estimates which are asymptotically more e0cient than the feasible generalized least-squares estimate when errors are spherically distributed. The result has an application in the improvement of the Graybill-Deal estimate of the common mean of several normal populations.

本文言語English
ページ(範囲)133-146
ページ数14
ジャーナルJournal of Statistical Planning and Inference
110
1-2
DOI
出版ステータスPublished - 2003 1 15
外部発表はい

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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