MULTIVARIATE BINARY DISCRIMINATION BY KERNEL METHOD
成果类型：
Article
署名作者：
AITCHISON, J; AITKEN, CGG
署名单位：
University of Glasgow
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/63.3.413
发表日期：
1976
页码：
413420
关键词：
摘要：
An extension of the kernel method of density estimation from continuous to multivariate binary spaces is described. Its simple nonparametric nature together with its consistency properties make it an attractive tool in discrimination problems, with some advantages over already proposed parametric counterparts. The method is illustrated by an application to a particular medical diagnostic problem. Simple extensions of the method to categorical data and to data of mixed binary and continuous form are indicated.