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Title
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Room
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Applying Finite Mixture Models
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M-International Salon D
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Date / Time
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Sponsor
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Type
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08/04/2001
1:00 PM
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5:00 PM
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ASA, IMS, JQT Review Board, Health Informatics, ASA, ENAR, WNAR, IMS, SSC, Section on Bayesian Stat. Sciences*, Biometrics Section*, Biopharmaceutical Section*, Business & Economics Statistics Section*, Section on Statistical Computing*, Section on Statistical Consulting*, Section on Statistical Education*, Section on Statistics & the Environment*, Section on Statistics in Epidemiology*, Section on Government Statistics*, Section on Statistical Graphics*, Section on Health Policy Statistics*, Section on Statistics and Marketing, Section on Physical & Engineering Sciences*, Section on Quality & Productivity*, Section on Risk Analysis, Social Statistics Section*, Section on Statistics in Sports*, Section on Survey Research Methods*, Section on Teaching of Statistics in the Health Sciences*, General Methodology, Classification Society of North America, Intl Chinese Statistical Association, Intl Indian Statistical Association, Natl Inst of Statistical Sciences, Natl Science Foundation, Cmte on Gay and Lesbian Concerns in Statistics, Cmte on Minorities in Statistics, Cmte on Privacy and Confidentiality, JBES, Technometrics, Chance, The American Statistician, Council of Chapters, ASA Atlanta Chapter, Caucus for Women in Statistics, Cmte on Professional Ethics, Mu Sigma Rho, Korean Statisticians in America, Merck & Co, Indian Statistical Institute, Gay & Lesbian Statisticians' Caucus, University of North Carolina Alumni, Texas A&M University Alumni, SMU Alumni & Friends, Interface Foundation of North American Stat Assn, Communications in Statistics, Census Research Meeting, Isolated Biostatisticians, Association of GCRC Statisticians, John Wiley & Sons, Isolated Statisticians, Cmte on Women in Statistics, Council of Sections, Cmte on Meetings, Cmte on Committees, Individual Membership Subcmte, JASA Book Review, ASA/SIAM Book Series, Carnegie Mellon Alumni & Faculty, Advisory Cmte on Continuing Education, Cmte on Statistics & Disabilities, JABES, JCGS, CIS, Cmte of Representatives to AAAS, Cmte on Career Development, Council of Presidents of Stat Societies, ASA Finance Committee, ASA/MAA Joint Cmte on Undergrad Stats, Academic Program Representatives, Cmte on ASA Archives & Historical Materials, Cmte on Membership, National Institute of Statistical Societies (NISS), Section on Nonparametric Statistics, Natl Research Ctr for Stats in the Environment, JSE, Cmte on Scientific Freedom and Human Rights, Intl Society for Bayesian Analysis (ISBA), Cmte on Statisticians in Defense and National Security, American Educational Research Association (AERA), Memorial Sessions, Amstat Online, Capital One, Household Credit Services, RAND Statistics Group, Cancer Center Biostatistics Directors, Forest Service Statisticians, Addison Wesley, Christian Statisticians, Hispanic Statisticians, Insightful Corporation, University of Pittsburgh, University of Connecticut, Eli Lilly and Company, Advisory Cmte on Teacher Enhancement, Committee on Publications, Science & Public Affairs Advisory Committee, Deming Lectureship Committee, STATS Magazine, Committee on Outreach, SPAIG, Development Committee, Iowa State University Alumni, Noether Award Committee, W J Youden Award in Interlaboratory Testing Cmte, JSM 2002 Program Committee, JSM Advisory Committee, Organizational Membership Committee, Special Subcommittee on Meetings, Key College Publishing, North Carolina State University, Duxbury/Thomson Learning, International Chinese Statistical Association, Statistics in Medicine, Cmte on Applied and Theoretical Statistics, ENAR, IMS, Section on Bayesian Stat. Sciences*, Biometrics Section*, Business & Economics Statistics Section*, Section on Statistical Computing*, Section on Statistical Consulting*, Section on Statistical Education*, Section on Statistics & the Environment*, Section on Statistics in Epidemiology*, Section on Government Statistics*, Section on Statistical Graphics*, Section on Health Policy Statistics*, Section on Physical & Engineering Sciences*, Section on Quality & Productivity*, Social Statistics Section*, Section on Statistics in Sports*, Section on Survey Research Methods*, Section on Teaching of Statistics in the Health Sciences*, General Methodology, Intl Indian Statistical Association, Cmte on Minorities in Statistics, Cmte on Privacy and Confidentiality, JASA, Theory and Methods, JASA, Applications, Caucus for Women in Statistics, Cmte on Women in Statistics, Council of Sections, Section on Nonparametric Statistics, ASA Alaska Chapter, ENAR, WNAR, IMS, Section on Bayesian Stat. Sciences*, Biometrics Section*, Business & Economics Statistics Section*, Section on Statistical Consulting*, Section on Statistical Education*, Section on Government Statistics*, Section on Statistical Graphics*, Section on Health Policy Statistics*, Section on Quality & Productivity*, Social Statistics Section*, Section on Survey Research Methods*, Section on Teaching of Statistics in the Health Sciences*, JASA, Theory and Methods, Caucus for Women in Statistics, Association of GCRC Statisticians, Cmte on Meetings, Washington Statisticial Society, Noether Award Committee, ENAR, IMS, SSC, Section on Statistical Consulting*, Section on Government Statistics*, Section on Health Policy Statistics*, Social Statistics Section*, WNAR, SSC, Cmte on Minorities in Statistics, Section on Statistical Graphics*, Section on Physical & Engineering Sciences*, Section on Quality & Productivity*
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Other
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Organizer:
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n/a
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Chair:
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n/a
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Discussant:
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CE Presenter
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Geoffrey Mclachlan
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Description
Finite mixtures of distributions have provided a mathematical-based approach to the statistical modeling of a wide variety of random phenomena. Because of their usefulness as an extremely flexible method modeling, finite mixture modes have continued to receive increasing attention over the years, both from a practical and theoretical point of view. Indeed, in the past decade the extent and the potential of the applications of finite mixture models have widened considerably. Fields in which mixture models have been successfully applied include astronomy, biology, economics, engineering, genetics, marketing, medicine, and psychiatry, among many other fields in the biological, physical, and social sciences. In these applications, finite mixture models underpin a variety of techniques in image analysis, and survival analysis, in addition to their more direct role in data analysis and inference of providing descriptive models for distributions.
Even with the advent of high-speed computers, there had been some reluctance in the past to fit mixture models to data of more than one dimension, possibly because of a lack of understanding of issues that arise with their fitting. They include the presence of multiple maxima in the mixture likelihood function and the unboundedness of the likelihood function in he case of normal components with unequal covariance matrices. But as the difficulties concerning these computational issues became to be properly understood and successfully addressed, it has led to the increasing use of mixture models in practice.
In this workshop, we shall provide an account of the major issues involved with modeling via finite mixture distributions. The emphasis is to be on the applications of finite mixture models, but there will be coverage of some of the important theoretical problems still to be resolved. The wide applicability of finite distributions for modeling random phenomena will be illustrated by their application to a variety of data sets arising from the various sciences. There is now available a number of software packages on the Web for the fitting of mixture models. A survey of these packages will be given in the workshop with particular emphasis on the presenter's own package called EMMIX. The latter has been substantially updated since JSM2000.
The workshop is aimed at statisticians in general, as well as to investigators working in the many diverse areas in which relevant use can be made of finite mixture models. Although it is anticipated that many in the audience will have majored in statistics, only a working knowledge of statistics will be needed to participate in the workshop.
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