Correlation analysis of extreme observations from a multivariate normal distribution
成果类型：
Article
署名作者：
Olkin, I; Viana, M
署名单位：
University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
刊物名称：
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN/ISSBN：
0162-1459
DOI：
10.2307/2291528
发表日期：
1995
页码：
1373-1379
关键词：
摘要：
In measuring visual acuity, the extremes of a set of normally distributed measures are of concern, together with one or more covariates. This leads to a model in which (X, Y-1, Y-2) are jointly normally distributed with Y-1, Y-2 exchangeable and (X, Y-i) having a common correlation. Inferential procedures are developed for correlations and linear regressions among X and the ordered Y values. This requires determination of the covariance matrix of X, Y-(1) = min{Y-1, Y-2} and Y(2) = max(Y-1, Y-2). The inadequacy of certain estimates that ignore the nonnormality of {X, Y-(1), Y-(2)} is also discussed. Although the bivariate case is emphasized because of the context of the visual acuity model, many results are given for the more general multivarjate case.