Fixed-sample optimal non-orthogonal estimating functions in the presence of nuisance parameters

Chih-Rung Chen*, Lih Chung Wang

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

In the paper, an important necessary and sufficient condition for a commonly used non-orthogonal estimating function to be fixed-sample optimal is proposed. The class of all fixed-sample optimal non-orthogonal estimating functions is characterized under the proposed condition. A simple counterex-ample without any fixed-sample optimal non-orthogonal estimating function is constructed to show that the proposed condition does not necessarily hold. The usefulness and applicability of the proposed method are illustrated by two classical examples with many nuisance parameters.

Original languageEnglish
Pages (from-to)653-671
Number of pages19
JournalTaiwanese Journal of Mathematics
Volume8
Issue number4
DOIs
StatePublished - 1 Jan 2004

Keywords

  • Estimating function
  • Fixed-sample optimal
  • Moore-Penrose inverse
  • Non-orthogonal
  • Nuisance parameter
  • Parameter of interest

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