Discrimination and Classification, Round 1
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.
KeywordsPosterior Probability Discriminant Function Prior Probability Covariance Matrice Normal Theory
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Suggested Further Reading
- Lachenbruch, P.A. 1975. Discriminant Analysis. New York: Hafner.Google Scholar
- Kaye, D.H., and Aickin, M. 1986. Statistical Methods in Discrimination Litigation. New York: Dekker.Google Scholar
- 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