平衡单向分类随机效应模型中的多个异常值检验

Abstract

Abstract: This paper studies the detection of multiple-outliers in balanced random-effects model of one-way classification. The authors derive the likelihood ratio test under the mean-shift model in random-effects. The distribution of test statistic is given and employed to obtain the test procedure. The authors also study the test of mean-shift outlier model in error variables, and a score test is used to identify the multiple-outliers in the data.

Key words: Random-effects model of one-way classification, Mutiple-outliers, Test, Score statistic

CLC Number:

62J99

Shi Lei; He Liping; Huang Mei.

Detection of Mutiple-outliers in Random-effects Model of Balanced One-way Classification

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Detection of Mutiple-outliers in Random-effects Model of Balanced One-way Classification

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