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Distribution free goodness of fit testing of grouped Bernoulli trials

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  • Roberts, Leigh A.

Abstract

Recently Khmaladze has shown how to ‘rotate’ one empirical process to another. We apply this methodology to goodness of fit tests for Bernoulli trials, generated by a single distributional family, but with covariates varying over the sample. Grouping the data, we demonstrate that goodness of fit tests after rotation to distribution free processes are easily computed, and exhibit high power to reject incorrect null hypotheses.

Suggested Citation

  • Roberts, Leigh A., 2019. "Distribution free goodness of fit testing of grouped Bernoulli trials," Statistics & Probability Letters, Elsevier, vol. 150(C), pages 47-53.
    • Handle: RePEc:eee:stapro:v:150:y:2019:i:c:p:47-53
    DOI: 10.1016/j.spl.2019.01.035
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    References listed on IDEAS

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    1. Khmaladze, Estate, 2017. "Distribution free testing for conditional distributions given covariates," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 348-354.
    2. Thuong T. M. Nguyen, 2017. "A new approach to distribution free tests in contingency tables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(2), pages 153-170, February.
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    Cited by:

    1. Estate V. Khmaladze, 2021. "Distribution-free testing in linear and parametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1063-1087, December.

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    1. Khmaladze, Estate, 2017. "Distribution free testing for conditional distributions given covariates," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 348-354.
    2. Estate V. Khmaladze, 2021. "Distribution-free testing in linear and parametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1063-1087, December.

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