The aim of this paper is to investigate the mixture index of fit in hypothesis testing problems from the point of view of robustness. The concept of contamination plot is introduced and an algorithm is proposed to determine it. Our algorithm is a remarkable application of the widely used EM algorithm by involving a two-phase M-step procedure. In the parametric phase the parameters of the model in the null hypothesis are estimated using the maximum likelihood method, while in the nonparametric phase the contaminating distribution is determined by a filling technique. It is proved that the objective function decreases monotonically during the iterations. Finally, the algorithm is applied and discussed when the hypothesis of independence is tested for contingency tables.
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Proceedings of the XXVI International Seminar on Stability Problems for Stochastic Models, Sovata-Bai, Romania, August 27 – September 2, 2006.
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Isp’any, M., Verdes, E. ON the Robustness of Mixture Index of Fit. J Math Sci 200, 432–440 (2014). https://doi.org/10.1007/s10958-014-1925-9
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DOI: https://doi.org/10.1007/s10958-014-1925-9