Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-15T17:24:04.540Z Has data issue: false hasContentIssue false
  • English
  • Français

On the Interpretation of Individual Variables in Multiple Discriminant Analysis

Published online by Cambridge University Press:  06 April 2009

Marvin J. Karson  and
Terrence F. Martell
Get access Rights & Permissions [Opens in a new window]

Extract

A number of articles have recently appeared in the literature dealing with the application of multiple discriminant analysis (MDA) to classification problems in the area of finance [2, 3, 7, 8, 13, 15]. The problem of assessing the importance of individual variables was an issue in these papers. The objective of this paper is to develop a ranking procedure for assessing the relative importance of the individual variables when it cannot be assumed that the group covariance matrices are equal. It is assumed that the analysis is for two groups. The ranking procedure we suggest relies upon the conditional deletion procedure based on a statistic used for solving the multivariate Behrens–Fisher problem.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 15 , Issue 1 , March 1980 , pp. 211 - 217
Copyright
Copyright © School of Business Administration, University of Washington 1980

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

[1]Box, G. E. P. “A General Distribution Theory for a Class of Likelihood Criteria.” Biometrika (08 1949).CrossRefGoogle Scholar
[2]Eisenbeis, R. A. “Pitfalls in the Application of Discriminant Analysis in Business, Finance and Economics.” Journal of Finance (06 1977).CrossRefGoogle Scholar
[3]Eisenbeis, R. A., and Altman, E. I.. “Financial Applications of Discriminant Analysis: A Clarification.” Journal of Financial and Quantitative Analysis (03 1978).Google Scholar
[4]Eisenbeis, R. A.; Gilbert, G. G.; and Avery, R. B.. “Investigating the Relative Importance of Individual Variables and Variable Subsets in Discriminant Analysis.” Communications in Statistics, Vol. 2, No. 3 (1973).CrossRefGoogle Scholar
[5]Holloway, L. N., and Dunn, O. J.. “The Robustness of Hotelling's T2.” Journal of the American Statistical Association (03 1967).Google Scholar
[6]James, G. S. “Tests of Linear Hypothesis in Univariate and Multivariate Analysis When the Ratios of the Population Variances Are Unknown.” Biometrika (04 1954).Google Scholar
[7]Joy, O. M., and Tollefson, J. O.. “On the Financial Application of Discriminant Analysis.” Journal of Financial and Quantitative Analysis (12 1975).Google Scholar
[8]Joy, O. M., and Tollefson, J. O. “Some Clarifying Comments on Discriminant Analysis.” Journal of Financial and Quantitative Analysis (03 1978).CrossRefGoogle Scholar
[9]Kshirsagar, A. M.Multivariate Analysis. New York: M. Dekker (1972).Google Scholar
[10]Lachenbruch, P. A.Discriminant Analysis. New York: Hafner Press (1975).Google Scholar
[11]Morrison, D. F.Multivariate Statistical Methods, 2nd ed.New York: McGraw–Hill Book Company (1976).Google Scholar
[12]Paksoy, C. et al. , “MVBFS: A Program Which Utilizes the Multivariate Behrens- Fisher Solution for Conditional Deletion in Two Group Discriminant Models.” Journal of Marketing Research (05 1977).Google Scholar
[13]Pinches, G. E. “Factors Influencing Classification Results from Multiple Discriminant Analysis.” Journal of Business Research (forthcoming).Google Scholar
[14]Sinkey, J. F. “A Multivariate Statistical Analysis of the Characteristics of Problem Banks.” The Journal of Finance (03 1975).CrossRefGoogle Scholar
[15]Scott, E. “On the Financial Applications of Discriminant Analysis: Comment.” Journal of Financial and Quantitative Analysis (03 1978).Google Scholar