Accession Number : ADA308972
Title : 'On Detecting Outliers in Mixed Populations'.
Descriptive Note : Scientific rept. no. 1,
Corporate Author : SOUTHERN METHODIST UNIV DALLAS TX DEPT OF STATISTICAL SCIENCE
Personal Author(s) : Gray, H. L. ; Sain, S. R. ; Frawley, W. H. ; Woodward, W. A.
PDF Url : ADA308972
Report Date : FEB 1996
Pagination or Media Count : 54
Abstract : In this report we introduce an operational methodology for detecting outliers in data which is a mixture of events from a variety of sources. The only assumption required is that the data contain no previous nuclear events. Thus ground truth data is not required. The method models the data as a mixture of two or more event types. It then develops a test statistic based on a modified likelihood ratio and the bootstrap T. test for outliers. The calculation of this statistic is accomplished by making use of clustering methods to initialize the EM algorithm which is then used to obtain the required maximum likelihood estimates.
Descriptors : *MAXIMUM LIKELIHOOD ESTIMATION, *SEISMIC DATA, *POPULATION(MATHEMATICS), ALGORITHMS, MONITORING, MULTIVARIATE ANALYSIS, STATISTICAL TESTS, RANDOM VARIABLES, STATISTICAL DATA, SEISMIC DETECTION, STATISTICAL SAMPLES, APPROXIMATION(MATHEMATICS), SEISMIC WAVES, NUCLEAR EXPLOSION DETECTION, SEISMIC DISCRIMINATION, EARTHQUAKES, DISTRIBUTION FUNCTIONS, GROUPS(MATHEMATICS).
Subject Categories : Seismology
Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE