Implementation and Applications of Bivariate Gaussian Mixture Decomposition
作者:
Michael Tarter,
Abraham Silvers,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1975)
卷期:
Volume 70,
issue 349
页码: 47-55
ISSN:0162-1459
年代: 1975
DOI:10.1080/01621459.1975.10480259
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
An interactive method for decomposing mixtures consisting of an arbitrary number of bivariate Gaussian components is described, which can handle problems currently attacked by cluster analysis methods. In contradistinction to most clustering methods, this procedure does not require selection of a metric or distance function with sample element arguments. Instead, estimates of population bivariate contours are examined graphically to yield estimates of subpopulation parameters. This approach is based on properties of the underlying population rather than on heuristic measures of distance between elements of a sample. Besides discussing the theory underlying this new class of procedures, several examples involving real and simulated data are presented.
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