Integrated likelihoods in models with stratum nuisance parameters

Riccardo De Bin, Nicola Sartori, Thomas A. Severini

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Frequentist inference about a parameter of interest in presence of a nuisance parameter can be based on an integrated likelihood function. We analyze the behaviour of inferential quantities based on such a pseudolikelihood in a two-index-asymptotics framework, in which both sample size and dimension of the nuisance parameter may diverge to infinity. We show that a properly chosen integrated likelihood largely outperforms standard likelihood methods, such as those based on the profile likelihood. These results are confirmed by simulation studies, in which comparisons with modified profile likelihood are also considered.

Original languageEnglish (US)
Pages (from-to)1474-1491
Number of pages18
JournalElectronic Journal of Statistics
Volume9
Issue number1
DOIs
StatePublished - 2015

Keywords

  • Modified profile likelihood
  • Non stationary autoregressive model
  • Profile likelihood
  • Profile score bias
  • Two-index asymptotics

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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