Article ID Journal Published Year Pages File Type
415636 Computational Statistics & Data Analysis 2007 8 Pages PDF
Abstract

Finite mixtures of parametric distributions are often used to model data of which it is known or suspected that there are sub-populations. Instead of a parametric model, a penalized likelihood smoothing algorithm is developed. The penalty is chosen to favor a log-concave result. The standard EM algorithm (“split and fit”) can be used. Theoretical results and applications are presented.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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