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B0894
Title: Maximum likelihood estimation of the latent class model through model boundary decomposition Authors:  Piotr Zwiernik - Universitat Pompeu Fabra (Spain) [presenting]
Abstract: The Expectation-Maximization (EM) algorithm is routinely used for the maximum likelihood estimation in the latent class analysis. However, the EM algorithm comes with no guarantees of reaching the global optimum. We study the geometry of the latent class model in order to understand the behavior of the maximum likelihood estimator. In particular, we characterize the boundary stratification of the binary latent class model with a binary hidden variable. For small models, such as for three binary observed variables, we show that this stratification allows exact computation of the maximum likelihood estimator. In this case we use simulations to study the performance of the EM algorithm.