We develop a suitable reweighting approach to deal with outliers when maximum-likelihood estimation is used to estimate latent class models. In such a context, the EM algorithm is used and the presence of singularities and spurious local maxima is common. The proposed method is motivated by an application aimed at finding clusters of offending behaviours.
Bartolucci, F., Francis, B., Pandolfi, S., Pennoni, F. (2015). Robust maximum likelihood estimation of latent class models. In Proceedings Vol. 1 30th International Workshop on Statistical Modelling (pp.94-99).
Robust maximum likelihood estimation of latent class models
PENNONI, FULVIA
2015
Abstract
We develop a suitable reweighting approach to deal with outliers when maximum-likelihood estimation is used to estimate latent class models. In such a context, the EM algorithm is used and the presence of singularities and spurious local maxima is common. The proposed method is motivated by an application aimed at finding clusters of offending behaviours.
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