Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415636 | Computational Statistics & Data Analysis | 2007 | 8 Pages |
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
Authors
Paul H.C. Eilers, M.W. Borgdorff,