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linear hypothesis testing using dlr metric
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نویسنده
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arabpour alireza ,mozafari mahdieh
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منبع
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journal of mahani mathematical research - 2013 - دوره : 2 - شماره : 2 - صفحه:73 -87
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چکیده
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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.
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کلیدواژه
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analysis of covariance ,confidence interval ,dlr metric ,fuzzy test statistic
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آدرس
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shahid bahonar university of kerman, faculty of mathematics andcomputer, department of statistics, ایران, higher education complex of bam, department of statistics, ایران
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پست الکترونیکی
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mozafari@bam.ac.ir
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Authors
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