Designs for discrimination between binary response models
type: Item
instance of: scholarly article
title: Designs for discrimination between binary response models
zbMATH Open document ID: 0641.62045
DOI: 10.1016/0378-3758(88)90050-X
author: Yukio Yanagisawa
published in: Journal of Statistical Planning and Inference
publication date: 1988-01-01T00:00:00Z
review text: We propose a test statistic for discrimination between alternative univariate binary response models which is asymptotically equivalent to the likelihood ratio statistic and Pearson's goodness of fit statistic. We propose an optimal design procedure. Under certain conditions we prove that the maximum value of the power can be obtained when the degrees of freedom of the test statistic is one. Several mathematical properties of the incomplete gamma function ratio and the non-central chi-squared distribution are required in the discussion and these are established.
Mathematics Subject Classification ID: 62K05
Mathematics Subject Classification ID: 62F03
Mathematics Subject Classification ID: 62J02
Mathematics Subject Classification ID: 62H15
zbMATH DE Number: 4044971
zbMATH Keywords: weighted residual sum of squares
zbMATH Keywords: discrimination
zbMATH Keywords: univariate binary response models
zbMATH Keywords: likelihood ratio statistic
zbMATH Keywords: Pearson's goodness of fit statistic
zbMATH Keywords: degrees of freedom
zbMATH Keywords: incomplete gamma function ratio
zbMATH Keywords: non- central chi-squared distribution
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 4044971