In this paper we present the finite mixture models approach to clustering of high dimensional data. The mixture resolving approach to cluster analysis has been addressed in a number of different ways; the underlying assumption is that the patterns to be clustered are drawn from one of several distributions, and the goal is to identify the parameters of each and (perhaps) their number. Finite mi...

Abstract The finite mixtures approach identifies homogeneous groups within the sample. data are aggregated into classes sharing similar patterns without any prior knowledge or assumption on clustering. These clusters characterized by group-specific regression coefficients to account for between heterogeneity. Two different approaches have been independently defined in literature compute this es...

Abstract This article presents basic ideas of finite mixture models in which the number components is known and distributions comprising are not assumed to come from any parametrically specified family. categorized under: Algorithms Computational Methods > Statistical Learning Exploratory Data Sciences Clustering Classification Graphical Analysis Nonparametric Models

We present a semiclassical three-fluid model for a Bose-condensed mixture of interacting Bose and Fermi gases confined in harmonic traps at finite temperature. The model is used to characterize the experimentally relevant behaviour of the equilibrium density profile of the fermions with varying composition and temperature across the onset of degeneracy, for coupling strengths relevant to a mixt...