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On modified discriminant analysis

Author

Listed:
  • Marcin Owczarczuk

    (Department of Applied Econometrics, Warsaw School of Economics)

Abstract
Discriminant analysis is mostly used to predict the value of a discrete dependent variable of an observation on the basis of a set of predictors. The commonly used criterion of the predictive power is the fraction of incorrectly predicted cases in the sample. In this article we construct a model for a modified discriminant problem. Namely to find a subpopulation of a given size having the highest percentage of observations of a chosen class. Our model maximizes the following criterion of the predictive power: the fraction of observations from chosen class in the found subpopulation.

Suggested Citation

  • Marcin Owczarczuk, 2007. "On modified discriminant analysis," Working Papers 6, Department of Applied Econometrics, Warsaw School of Economics.
    • Handle: RePEc:wse:wpaper:6
    as

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    File URL: http://kolegia.sgh.waw.pl/pl/KAE/struktura/IE/struktura/ZES/Documents/Working_Papers/aewp06-07.pdf
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    References listed on IDEAS

    as
    1. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-531, May.
    2. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    discriminant analysis; semiparametric estimation; smoothing; binary response;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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