A finite mixture model to simultaneously cluster the rows and columns of two-mode ordinal data matrix is proposed. Due to the numerical intractability of the likelihood function, estimation of model parameters is based on composite likelihood (CL) methods and essentially reduces to a computationally efficient Expectation-Maximization type algorithm. The performance of the proposed approach is discussed on both simulated and real datasets. The results are encouraging and would deserve further discussion.
Model-based approach to biclustering ordinal data / Ranalli, Monia; Martella, Francesca. - (2020), pp. 1177-1182. (Intervento presentato al convegno 50th Scientific Meeting on the Italian Statistical Society tenutosi a Pisa).
Model-based approach to biclustering ordinal data
Monia Ranalli
;francesca Martella
2020
Abstract
A finite mixture model to simultaneously cluster the rows and columns of two-mode ordinal data matrix is proposed. Due to the numerical intractability of the likelihood function, estimation of model parameters is based on composite likelihood (CL) methods and essentially reduces to a computationally efficient Expectation-Maximization type algorithm. The performance of the proposed approach is discussed on both simulated and real datasets. The results are encouraging and would deserve further discussion.| File | Dimensione | Formato | |
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