Improved chi-squared tests for a composite hypothesis

Anthony Ennos, Yoshihide Kakizawa

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The Bartlett-type adjustment is a higher-order asymptotic method for improving the chi-squared approximation to the null distributions of various test statistics. Though three influential papers were published in 1991-Chandra and Mukerjee (1991) [8], Cordeiro and Ferrari (1991) [12] and Taniguchi (1991) [36] in alphabetical order, the only CF-approach has been frequently applied in the literature during the last two decades, provided that asymptotic expansion for the null distribution of a given test statistic is available. Revisiting the CM/T-approaches developed in the absence of a nuisance parameter, this paper suggests general adjustments for a class of test statistics that includes, in particular, the likelihood ratio, Rao's and Wald's test statistics in the presence of a nuisance parameter. © 2012 Elsevier Inc.
    Original languageEnglish
    Pages (from-to)141-161
    Number of pages20
    JournalJournal of Multivariate Analysis
    Volume107
    Publication statusPublished - May 2012

    Keywords

    • Asymptotic expansion
    • Bartlett-type adjustment
    • Chi-squared approximation
    • Composite hypothesis
    • Nuisance parameter

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