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Abstract: Exponential families are the workhorses of parametric modelling theory. Onereason for their popularity is their associated inference theory, which is veryclean, both from a theoretical and a computational point of view. One way inwhich this set of tools can be enriched in a natural and interpretable way isthrough mixing. This paper develops and applies the idea of local mixturemodelling to exponential families. It shows that the highly interpretable andflexible models which result have enough structure to retain the attractiveinferential properties of exponential families. In particular, results onidentification, parameter orthogonality and log-concavity of the likelihood areproved.



Autor: Karim Anaya-Izquierdo, Paul Marriott

Fuente: https://arxiv.org/







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