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CHANCE OF MISCLASSIFICATION IN THE CASE OF SEVERAL NORMAL POPULATIONS

dc.contributor.authorPaek, Pil S.en_US
dc.contributor.authorKshirsagar, Anant M.en_US
dc.date.accessioned2010-06-01T22:03:34Z
dc.date.available2010-06-01T22:03:34Z
dc.date.issued1996-04en_US
dc.identifier.citationPaek, Pil S.; Kshirsagar, AnantM. (1996). "CHANCE OF MISCLASSIFICATION IN THE CASE OF SEVERAL NORMAL POPULATIONS." Australian & New Zealand Journal of Statistics 38(1): 75-82. <http://hdl.handle.net/2027.42/75085>en_US
dc.identifier.issn1369-1473en_US
dc.identifier.issn1467-842Xen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/75085
dc.description.abstractWhen a new observation is to be classified into one of several multivariate normal populations with different means and the same covariance matrix, by Rao's method of scoring, the chance of misclassification is expressed as a multiple integral. This paper gives a practical method of obtaining reasonable approximations to this integral by using tables prepared by Gibbons, Olkin & Sobel (1977) for a different task.en_US
dc.format.extent377561 bytes
dc.format.extent3109 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Ltden_US
dc.rights1996 Australian Statistical Publishing Association Inc.en_US
dc.subject.otherChance of Misclassificationen_US
dc.subject.otherSeveral Normal Populationsen_US
dc.titleCHANCE OF MISCLASSIFICATION IN THE CASE OF SEVERAL NORMAL POPULATIONSen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDept of Biostatistics, University of Michigan, Ann Arbor, MI 48109-2029.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/75085/1/j.1467-842X.1996.tb00365.x.pdf
dc.identifier.doi10.1111/j.1467-842X.1996.tb00365.xen_US
dc.identifier.sourceAustralian & New Zealand Journal of Statisticsen_US
dc.identifier.citedreferenceGibbons, J.D., Olkin, I. & Sobel, M. ( 1977 ). Selecting and Ordering Populations: A New Statistical Methodology. New York: John Wiley and Sons, Inc.en_US
dc.identifier.citedreferenceHochberg, Y. & Tamhane, A.C. ( 1987 ). Multiple Comparison Procedures. New York: John Wiley and Sons, Inc.en_US
dc.identifier.citedreferenceKimball, A.W. ( 1951 ). On dependent tests of significance in the analysis of variance. Ann. Math. Statist. 22, 600 – 602.en_US
dc.identifier.citedreferenceKshirsagar, A.M. & Arsenven, E. ( 1975 ). A note on the equivalency of two discriminant procedures. Amer. Statist. 29, 38 – 39.en_US
dc.identifier.citedreferenceLachenbruch, P.A. ( 1965 ). Estimation of Error Rates in Discriminant Analysis. PhD dissertation, University of California, Los Angeles.en_US
dc.identifier.citedreferenceMcLachlan, G.J. ( 1992 ). Discriminant Analysis and Statistical Pattern Recognition. New York: Wiley.en_US
dc.identifier.citedreferencePark, P.S. ( 1994 ). Errors of Misclassification in Discriminant Analysis. PhD thesis, University of Michigan, Dept of Biostatistics, Ann Arbor, Michigan.en_US
dc.identifier.citedreferencePenrose, L.S. ( 1947 ). Some notes on discrimination. Ann. Eugen. 13, 228.en_US
dc.identifier.citedreferenceRao, C.R. ( 1973 ). Linear Statistical Inference and Its Applications, 2nd edition. New York: John Wiley and Sons, Inc.en_US
dc.identifier.citedreferenceSchervish, M.J. ( 1981 ). Asymptotic expansions for the means and variances of error rates. Biometrika 68, 295 – 299.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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