Estimation and testing in large binary contingency tables

W.C.M. Kallenberg

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    Abstract

    Very sparse contingency tables with a multiplicative structure are studied. The number of unspecified parameters and the number of cells are growing with the number of observations. Consistency and asymptotic normality of natural estimators are established. Also uniform convergence of the estimators to the parameters is investigated, and an application to the construction of confidence intervals is presented. Further, a family of goodness-of-fit tests is proposed for testing multiplicativity. It is shown that the test statistics are asymptotically normal. The results can be applied in such different fields as production testing or psychometrics.
    Original languageEnglish
    Pages (from-to)205-226
    JournalJournal of multivariate analysis
    Volume30
    Issue number2
    DOIs
    Publication statusPublished - 1989

    Keywords

    • uniform convergence
    • asymptotic normality
    • divergence measures
    • Goodness of Fit
    • multiplicative structure
    • Sparse contingency tables
    • Consistency

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