Discrimination and Classification, Round 1

  • Bernard Flury
Part of the Springer Texts in Statistics book series (STS)

Abstract

Discriminant analysis and related methods, treated in Chapters 5 to 7, are the central topics of this course. Chapter 5 gives an introduction on a mostly descriptive level, ignoring questions of statistical inference. The mathematical level of Chapter 5 is moderate, and all concepts are explained at great length, hoping that even students without a strong mathematical background will be able to master most of the material. Chapter 6 gives an introduction to problems of statistical inference that arise naturally from the setup of discriminant analysis: testing for equality of mean vectors, confidence regions for mean vectors, and related problems for discriminant functions. Then Chapter 7 resumes the classification theory on a more abstract level and gives brief introductions to related topics, such as logistic regression and multivariate analysis of variance.

Keywords

Posterior Probability Discriminant Function Prior Probability Covariance Matrice Normal Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Suggested Further Reading

  1. Hand, D.J., 1981. Discrimination and Classification. New York: Wiley.MATHGoogle Scholar
  2. Mardia, K.V., Kent, J.T., and Bibby, J.M. 1979. Multivariate Analysis. London: Academic Press.MATHGoogle Scholar
  3. McLachlan, G.J. 1992. Discriminant Analysis and Statistical Pattern Recognition. New York: Wiley.CrossRefGoogle Scholar
  4. Seber, G.A.F. 1984. Multivariate Obervations. New York: Wiley.CrossRefGoogle Scholar
  5. Fisher, R.A. 1936. The use of multiple measurements in taxonomic problems. Annals of Eugenics 7, 179–188.CrossRefGoogle Scholar
  6. Anderson, T.W. 1984. An Introduction to Multivariate Statistical Analysis, 2nd ed. New York: Wiley.MATHGoogle Scholar
  7. Lachenbruch, P.A. 1975. Discriminant Analysis. New York: Hafner.Google Scholar
  8. Lachenbruch, P.A., and Mickey, R. 1968. Estimation of error rates in discriminant analysis. Technometrics 10, 1–11.MathSciNetCrossRefGoogle Scholar
  9. Kaye, D.H., and Aickin, M. 1986. Statistical Methods in Discrimination Litigation. New York: Dekker.Google Scholar
  10. Rao, C.R., Bose R.C. 1970 Inference on discriminant function coefficients, Essays in Probability and Statistics, University of North Carolina Press, University of North Carolina Press, 587-602Google Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Bernard Flury
    • 1
  1. 1.Department of MathematicsIndiana UniversityBloomingtonUSA

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