Title of article :
LINEAR HYPOTHESIS TESTING USING DLR METRIC
Author/Authors :
ARABPOUR ، ALIREZA - SHAHID BAHONAR UNIVERSITY OF KERMAN , MOZAFARI ، MAHDIEH - HIGHER EDUCATION COMPLEX OF BAM
Abstract :
Several practical problems of hypotheses testing can be under a general linear model analysis of variance which would be examined. In analysis of variance, when the response random variable Y , has linear relationship with several random variables X, another important model as analysis of covariance can be used. In this paper, assuming that Y is fuzzy and using DLR metric, a method for testing the linear hypothesis has been proposed based on fuzzy techniques. In fact, in this method a set of con dence intervals has been used for creating fuzzy test statistic and fuzzy critical values. In addition, the pro- posed method has been mentioned for the reforming of the hypothesis testing when there is an uncertaity in accepting or rejecting hypotheses. Finally, by presenting two examples this method is illustrated. The result are illustrated by the means of some case studies.
Keywords :
Analysis of covariance , Confidence interval , DLR metric , Fuzzy test statistic
Journal title :
journal of mahani mathematical research center
Journal title :
journal of mahani mathematical research center