Checking for normality in linear mixed models

来源 :中国科学：数学英文版 | 被引量 : 0次 | 上传用户：sysbot

【摘要】

：

线性混合模型流行地被用来适合连续纵的数据，并且随机的效果通常被假定有正常分发。然而，这个假设需要被测试以便进一步的分析能被继续很好。在这份报纸，我们考虑 Baringhaus-He

【作者】

：

Ping Wu (1) pwu@stat.ecnu.edu.

【机构】

：

EChinaNormalUniv,YunnanUnivFinance&,Econ,HongKongBaptistUniv,ShanghaiNormalUniv

【出处】

：

中国科学：数学英文版

【发表日期】

：

2012年4期

【关键词】

：

线性混合模型模型检查经验特征函数随机效应纵向数据正态分布样本大小蒙特卡洛 linear mixed models estimated best

【基金项目】

：

supported in part by a grant of Research Grants Council of Hong Kong,and National Natural Science Foundation of China (Grant No. 11101157)

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线性混合模型流行地被用来适合连续纵的数据，并且随机的效果通常被假定有正常分发。然而，这个假设需要被测试以便进一步的分析能被继续很好。在这份报纸，我们考虑 Baringhaus-Henze-Epps-Pulley (BHEP ) 测试，它基于实验典型功能。不同于他们的盒子，我们考虑检查是 unobservable 的随机的效果的规度，测试应该基于他们的预言者。测试对全球选择是一致的，并且对以某个率收敛到 0 的选择任意地关上到 1/ 的本地人敏感 ? n 的 n1/\\sqrt n 样品尺寸。而且，克服测试

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Checking for normality in linear mixed models

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