Error Rates of a Robust Classification Procedure...

Error Rates of a Robust Classification Procedure Based on Dichotomous and Continuous Random Variables

Abstract

The error rates of the classification procedure based on Tiku's (1967, 1988) MML estimators are evaluated and shown to be smaller than those of the Chang and Afifi (1974) procedure which is based on sample means and sample variances.

Authors

Tuku ML; Balakrishnan N; Ambagaspittya RS

Journal

Communications in Statistics - Simulation and Computation, Vol. 18, No. 2, pp. 571–588

Publisher

Taylor & Francis

Publication Date

January 1, 1989

DOI

10.1080/03610918908812777

ISSN

0361-0918

Associated Experts

Narayanaswamy Balakrishnan

Professor, Faculty of Science

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Labels

Fields of Research (FoR)

49 Mathematical sciences 4905 Statistics 46 Information and computing sciences

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