Bøker av Geoffrey J. (The University of Queensland McLachlan

This collection includes: Finite Mixture Models By: McLachlan ISBN: 9780471006268                            Describes the formulations of the finite mixture approach, details its methodology, discusses aspects of its implementation, and illustrates its application in many common statistical contexts. The EM Algorithm and Extensions, 2nd Edition By: McLachlan ISBN: 9780471201700                           The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. Analyzing Microarray Gene Expression Data By: McLachlan ISBN: 9780471226161                            Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results. Discriminant Analysis and Statistical Pattern Recognition By: McLachlan ISBN: 9780471691150                           This book provides a modern, comprehensive, and systematic account of discriminant analysis and statistical pattern recognition.

Since its inception in 1977, the Expectation-Maximization (EM) algorithm has been the subject of intense scrutiny, dozens of applications, numerous extensions, and thousands of publications. The algorithm and its extensions are now standard tools applied to incomplete data problems in virtually every field in which statistical methods are used.

Available in paperback for the first time, this bestseller provides a systematic account of the subject area, while concentrating on the most recent advances in the field. While the focus is on practical considerations, both theoretical and practical issues are explored.

A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies.

Finite mixture models are typically used where the population being studied is heterogeneous in composition. This work aims to offer an up-to-date account of the major issues involved with finite modelling. There is a practical emphasis on the applications of mixture models.