Parametric robust inference about regression parameters for the correlation coefficient

Chien Hung Chen, Tsung Shan Tsou

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This article establishes a robust likelihood function about regression parameters for the correlation coefficients modeled in a generalized linear model fashion. The validity of the proposed likelihood requires no knowledge of the true underlying distributions, so long as they have finite fourth moments. The efficacy of the robust methodology is shown via simulations. The asymptotic variance of the maximum-likelihood estimate and the empirical error probabilities of the resultant robust likelihood ratio test are specifically exhibited.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalStatistics
Volume41
Issue number1
DOIs
StatePublished - Feb 2007

Keywords

  • Bivariate normal
  • Correlation coefficient
  • Robust likelihood

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