Bayesian Nonparametric Mixture Models

Introduction. Dirichlet Process Mixture Models: Theory and Methods. Dirichlet Process Mixture Models: Posterior Inference. Nonparametric Mixture Methodology for Random Effects Distributions and Generalized Linear Models. Bayesian Nonparametric Mixture Modeling for Regression Settings. Dependent Nonparametric Mixture Models. Spatial and Spatio-Temporal Modeling with Dependent Nonparametric Priors. More General Nonparametric Mixture Models. Conclusions/Discussion.

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• Probabilidade e Estatística
• Engenharia do controlo automático