Accession Number:

AD0749972

Title:

Asymptotic Evaluation of the Probabilities of Misclassification by Linear Discriminant Functions

Descriptive Note:

Technical rept.

Corporate Author:

STANFORD UNIV CA DEPT OF STATISTICS

Personal Author(s):

Report Date:

1972-09-28

Pagination or Media Count:

24.0

Abstract:

Linear discriminant functions are used to classify an observation as coming from one of two normal populations with common covariance matrices and different means when samples are used to estimate the parameters of the distributions. Okamotos asymptotic expansion of the distribution of the classification statistic W is compared with Andersons expansion for the Studentized W that is, W standardized by estimates of its mean and standard deviation. Some numerical evaluations of the term of order of the reciprocal of the sample sizes is given. The uses of the two approximate distributions are discussed.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE