In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
This paper describes nonparametric Bayesian treatments for analyzing records containing occurrences of items. The introduced model retains the strength of previous approaches that...
We consider mixtures of parametric densities on the positive reals with a normalized generalized gamma process (Brix, 1999) as mixing measure. This class of mixtures encompasses t...
Raffaele Argiento, Alessandra Guglielmi, Antonio P...
The Hidden Markov Model (HMM) has been widely used in many applications such as speech recognition. A common challenge for applying the classical HMM is to determine the structure...