Discriminant Analysis Based on Binary and Continuous Variables
作者:
Ching-Tsao Tu,
Chien-Pai Han,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1982)
卷期:
Volume 77,
issue 378
页码: 447-454
ISSN:0162-1459
年代: 1982
DOI:10.1080/01621459.1982.10477831
出版商: Taylor & Francis Group
关键词: Double-discriminant function;Comparison of discriminant procedures;Point-biserial model;Double inverse sampling;Probability of misclassification;Error rate
数据来源: Taylor
摘要:
An observation consisting of both binary and continuous variables may be classified into one of two populations by the double-discriminant function based on the point-biserial model. When the parameters are unknown or partially known, a sample double-discriminant function is obtained by replacing the unknown parameters by their sample estimates. A sampling scheme referred to as the double inverse sampling is proposed to ensure nonsingularity of the sample covariance matrices. An asymptotic expansion for the distribution of the sample double-discriminant function is given under the double inverse sampling scheme. Comparisons of three classification procedures—double-discriminant function,X-out procedure, andX-continuous procedure—are made.
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