The use of the statistical technique of mixture model analysis as a tool for early prediction of fault-prone program modules is investigated. The Expectation-Maximum likelihood (E...
Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding pro...
Ross K. Shepherd, Theo H. E. Meuwissen, John A. Wo...
The mixmod (mixture modeling) program fits mixture models to a given data set for the purposes of density estimation, clustering or discriminant analysis. A large variety of algor...
Abstract. It has been recently demonstrated that the classical EM algorithm for learning Gaussian mixture models can be successfully implemented in a decentralized manner by resort...
Nikos A. Vlassis, Yiannis Sfakianakis, Wojtek Kowa...
R package flexmix provides flexible modelling of finite mixtures of regression models using the EM algorithm. Several new features of the software such as fixed and nested var...