A modified likelihood ratio statistic for some nonregular models

Thomas A Severini*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Higher-order approximations to the distribution of the likelihood ratio statistic are considered for a class of nonregular models in which the maximum likelihood estimator of the parameter of interest is asymptotically distributed according to an exponential, rather than a normal, distribution. Asymptotic behaviour of this type often arises when the boundary of the support of the distributions under consideration depends on 9. A modified likelihood ratio statistic is proposed that follows its asymptotic distribution to a high degree of approximation, and this statistic is illustrated on several examples.

Original languageEnglish (US)
Pages (from-to)603-612
Number of pages10
JournalBiometrika
Volume91
Issue number3
DOIs
StatePublished - Dec 1 2004

Keywords

  • Higher-order asymptotic theory
  • Likelihood ratio approximation
  • Maximum likelihood
  • Unknown endpoint

ASJC Scopus subject areas

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

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