Applications of measures of uncertainty in discriminant analysis

  • David Hirst
  • Ian Ford
  • Frank Critchley
Classifiation Techniques
Part of the Lecture Notes in Computer Science book series (LNCS, volume 301)


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  1. Aitchison, J. & Dunsmore, I. R. (1975). Statistical Prediction Analysis, Cambridge University Press.Google Scholar
  2. Anderson, J.A. (1972). Separate sample logistic discrimination. Biometrika, 59, 19–35.Google Scholar
  3. Ambergen, A.W. and Schaafsma, W. (1984). Interval estimates for posterior probabilities, applications to Border Cave. In Multivariate Statistical Methods in Physical Anthropology. (G.M. Van Vark & W.W. Howells, eds.). D. Reidel Publishing Company.Google Scholar
  4. Critchley, F. and Ford, I. (1984). On the covariance of two noncentral F random variables and the variance of the estimated linear discriminant function. Biometrika, 71, 637–8.Google Scholar
  5. Critchley, F. and Ford, I. (1985). Interval estimation in discrimination: the multivariate normal equal covariance case. Biometrika, 72, 109–116.Google Scholar
  6. Critchley, F., Ford., I. and Hirst, D. (1988). An evaluation of methods of interval estimation for the odds ratio in discrimination. To appear in the Proceedings of the Fifth International Symposium on Data Analysis and Informatics, Versailles, 1987. North Holland.Google Scholar
  7. Critchley, F., Ford, I. and Rijal, O. (1987). Uncertainty in discrimination. Proceedings of the Conference DIANA II held in Liblice, 1986. Mathematical Institute of the Czechoslovak Academy of Sciences, Prague, 83–106.Google Scholar
  8. Critchley, F., Ford, I. and Rijal, O. (1988). Interval estimation based on the profile likelihood: strong Lagrangian theory with applications to discrimination. Biometrika, 75, 21–28.Google Scholar
  9. Davis, A.W. (1987). Moments of linear discriminant functions, and an asymptotic confidence interval for the log odds ratio. Biometrika, 74, 829–840.Google Scholar
  10. Hirst, D., Ford, I. and Critchley, F. (1988). Interval estimation in discrimination a simulation study. Submitted for publication.Google Scholar
  11. Kalbfleisch, J.G. and Sprott, D.A. (1970). Application of likelihood methods to models involving large numbers of parameters. J.R. Statist. Soc., B, 32, 175–208.Google Scholar
  12. Kalbfleisch, J.G. (1979). Probability and Statistical Inference II. New York: Springer-Verlag.Google Scholar
  13. Moran, M.A. and Murphy, B.J. (1979). A closer look at two alternative methods of statistical discrimination. Appl. Statist., 28, 223–232.Google Scholar
  14. Peers, H.W. & Iqbal, M. (1985). Asymptotic expansions for confidence limits in the presence of nuisance parameters with applications. J.R. Statist. Soc. B, 47, 547–554.Google Scholar
  15. Rigby, R.A. (1982). A credibility interval for the probability that a new observation belongs to one of two multivariate normal populations. J.R. Statist. Soc. B, 44, 212–220.Google Scholar
  16. Schaafsma, W. (1982). Selecting variables in discriminant analysis for improving upon classical procedures. In Handbook of Statistics. Vol.2 P.R. Krishnaiah and L.N. Kanal, eds), Amsterdam, North Holland.Google Scholar
  17. Schaafsma, W. and Van Vark, G.N. (1979). Classification and discrimination problems with applications II. Statist. Neerlandica, 33, 91–126.Google Scholar
  18. Van der Sluis, D.M. and Schaafsma, W. (1984). POSCON — a decision-support system in diagnosis and prognosis based on a statistical approach. In Compstat 1984 (T. Havranek et al. eds) Vienna: Physica-Verlag.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • David Hirst
    • 1
  • Ian Ford
    • 1
  • Frank Critchley
    • 2
  1. 1.Department of StatisticsUniversity of GlasgowGlasgow
  2. 2.Department of StatisticsUniversity of WarwickCoventry

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