Accession Number : ADA186032
Title : Variable Selection in Logistic Regression.
Descriptive Note : Technical rept.,
Corporate Author : PITTSBURGH UNIV PA CENTER FOR MULTIVARIATE ANALYSIS
Personal Author(s) : Bai, Z D ; Krishnaiah, P R ; Zhao, L C
PDF Url : ADA186032
Report Date : Jun 1987
Pagination or Media Count : 20
Abstract : In many situations, we are interested in selection of important variables which are adequate for prediction under a logistic regression model. In this paper, some selection procedures based on the information theoretic criteria are proposed, and these procedures are proved to be strongly consistent. Keywords: Maximum likelihood estimation; Multivariate analysis; Asymptotic expansion.
Descriptors : *REGRESSION ANALYSIS, *VARIABLES, ASYMPTOTIC SERIES, INFORMATION THEORY, LOGISTICS, MATHEMATICAL MODELS, MAXIMUM LIKELIHOOD ESTIMATION, SELECTION, MULTIVARIATE ANALYSIS, MATHEMATICAL PREDICTION
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE