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Pearson chi-square estimator and test for log-linear models with expected frequencies subject to linear constraints

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  • Bonett, Douglas G.

Abstract

The minimum Pearson chi-square estimator and test are defined for multinomial log-linear models with expected frequencies subject to linear constraints. The minimum Pearson chi-square estimate defined here yields predicted cell frequency estimates that, unlike the maximum likelihood estimates, minimize the popular Pearson chi-square test statistic.

Suggested Citation

  • Bonett, Douglas G., 1989. "Pearson chi-square estimator and test for log-linear models with expected frequencies subject to linear constraints," Statistics & Probability Letters, Elsevier, vol. 8(2), pages 175-177, June.
    • Handle: RePEc:eee:stapro:v:8:y:1989:i:2:p:175-177
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    Cited by:

    1. N. Martín & L. Pardo, 2008. "Minimum phi-divergence estimators for loglinear models with linear constraints and multinomial sampling," Statistical Papers, Springer, vol. 49(1), pages 15-36, March.

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