An optimal estimating equation based on the first three cumulants

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

For improving on quasilikelihood estimation two types of quadratic estimating equations have been proposed, one based on the Edgeworth expansion, the other on the generalisation of the quasi-score. The first requires that the skewness of observations has a small departure from the exponential family; the second requires the knowledge of both skewness and kurtosis. We introduce an optimal quadratic estimating equation applicable when the skewness is not small and the kurtosis is unknown. Apart from optimality, the manner in which skewness is incorporated ensures that its misspecification does not affect √n-consistency, and that the estimator enjoys an invariance property akin to that of the bias-corrected maximum likelihood estimate. Simulations indicate a solid improvement in accuracy.

Original languageEnglish (US)
Pages (from-to)103-114
Number of pages12
JournalBiometrika
Volume85
Issue number1
DOIs
StatePublished - Jan 1 1998

All Science Journal Classification (ASJC) codes

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

Fingerprint Dive into the research topics of 'An optimal estimating equation based on the first three cumulants'. Together they form a unique fingerprint.

  • Cite this