George Mason University
CSI/Statistics Colloquium Series
Seminar Announcement

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Robust Mixture Modeling and Applications

David Scott


Rice University


ABSTRACT We investigate the use of the popular nonparametric integrated squared error criterion, but for use in parametric estimation. Of particular interest are the problems of fitting normal mixture densities and linear regression. The algorithm is in the class of minimum distance estimators. We discuss some of its theoretical properties and compare it to maximum likelihood. The robustness of the procedure is demonstrated by example. The criterion may be applied in a wide range of models. Two case studies are given: an application to a series of yearly household income samples as well as a more complex application involves estimating an economic frontier function of U.S. banks where the data are assumed to be noisy. Extensions to clustering and discrimination problems follow.

Friday, October 29, 1999
George W. Johnson Center, Assembly Room B
Seminar at 10:45 a.m.
Refreshments at 10:30 a.m.
For the 1999 Fall Seminar Schedule, go to
http:www.science.gmu.edu/statseminars