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Title: Parameter estimation in biclassified blockmodels as mixture of contingency tables via the EM algorithm Authors:  Marianna Bolla - Institute of Mathematics, Technical University of Budapest (Hungary) [presenting]
Fatma Abdelkhalek - Institute of Mathematics Technical University of Budapest (Hungary)
Jozsef Mala - Institute of Mathematics Technical University of Budapest (Hungary)
Abstract: A random contingency table model is introduced, where the entries are independent beta-distributed with parameters depending on their row and column labels. Sufficient statistics are specified, and based on them, an algorithm is given to find the MLE of the parameters, together with convergence proof. The model is extended to the multiclass scenario, where for fixed number of biclusters, the parameters of the beta-distributed entries also depend on their row and column cluster memberships. To find the clusters and estimate the parameters, an EM iteration for mixtures of exponential-family distributions is used. The algorithm is applicable to microarrays, and a genetic example is presented.