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• W2014207836 abstract "Abstract The problem of obtaining the maximum probability 2 × c contingency table with fixed marginal sums, R = (R 1, R 2) and C = (C 1, … , C c ), and row and column independence is equivalent to the problem of obtaining the maximum probability points (mode) of the multivariate hypergeometric distribution MH(R 1; C 1, … , C c ). The most simple and general method for these problems is Joe's (Joe, H. (1988 Joe, H. 1988. Extreme probabilities for contingency tables under row and column independence with application to Fisher's exact test. Commun. Statist. Theory Meth., 17(11): 3677–3685. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). Extreme probabilities for contingency tables under row and column independence with application to Fisher's exact test. Commun. Statist. Theory Meth. 17(11):3677–3685.) In this article we study a family of MH's in which a connection relationship is defined between its elements. Based on this family and on a characterization of the mode described in Requena and Martín (Requena, F., Martín, N. (2000 Requena, F. and Martín, N. 2000. Characterization of maximum probability points in the multivariate hypergeometric distribution. Statist. Probab. Lett., 50: 39–47. [Google Scholar]). Characterization of maximum probability points in the multivariate hypergeometric distribution. Statist. Probab. Lett. 50:39–47.), we develop a new method for the above problems, which is completely general, non recursive, very simple in practice and more efficient than the Joe's method. Also, under weak conditions (which almost always hold), the proposed method provides a simple explicit solution to these problems. In addition, the well-known expression for the mode of a hypergeometric distribution is just a particular case of the method in this article." @default.
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• W2014207836 date "2003-01-08" @default.
• W2014207836 modified "2023-09-27" @default.
• W2014207836 title "The Maximum Probability 2 × <i>c</i>Contingency Tables and the Maximum Probability Points of the Multivariate Hypergeometric Distribution" @default.
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• W2014207836 doi "https://doi.org/10.1081/sta-120022706" @default.
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