Estimating functions and approximate conditional likelihood

Kung Yee Liang

Research output: Contribution to journalArticlepeer-review

Abstract

The approximate conditional likelihood method proposed by Cox & Reid (1987) is applied to the estimation of a scalar parameter Θ, in the presence of nuisance parameters. The estimating function of Θ based on the approximate conditional likelihood is shown to be preferable to that based on the profile likelihood. A sufficient condition for both approaches to be equivalent is given. The role of parameter orthogonality is emphasized. Several examples including bivariate normal means with known coefficient of variation are presented.

Original languageEnglish (US)
Pages (from-to)695-702
Number of pages8
JournalBiometrika
Volume74
Issue number4
DOIs
StatePublished - Dec 1 1987

Keywords

  • Asymptotics
  • Conditional inference: Estimating function
  • Nuisance parameter
  • Parameter orthogonality

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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