Asymptotic Analysis of Mis-Classified Linear Mixed Models

IF 1.5 3区 数学 Q2 STATISTICS & PROBABILITY Statistica Sinica Pub Date : 2023-01-01 DOI:10.5705/ss.202023.0082
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Abstract

Analysis of Mis-Classified Linear Mixed Models
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误分类线性混合模型的渐近分析
研究了类错配对线性混合模型分析的影响。在这里,错误分类意味着与随机效应相关的某些类或组不匹配。这种错误分类问题在现代数据科学中变得越来越普遍,包括有意和无意的错误分类。故意错误规范的一个重要案例与差异隐私有关;而在分类混合模型预测中会出现非故意的误规范。我们的研究表明,当错分类群数的比例在适当意义上渐近可忽略时,最大似然估计量和限制最大似然估计量的标准渐近性质,包括一致性和渐近正态性,在错误分类下仍然有效。仿真研究的实证结果完全支持了我们的理论发现。考虑一个实际数据示例。
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相关文献
Mis-Specification Analysis of Linear Degradation Models
IF 5.9 2区 计算机科学IEEE Transactions on ReliabilityPub Date : 2009-08-07 DOI: 10.1109/TR.2009.2026784
Chien-Yu Peng;Sheng-Tsaing Tseng
来源期刊
Statistica Sinica
Statistica Sinica 数学-统计学与概率论
CiteScore
2.10
自引率
0.00%
发文量
82
审稿时长
10.5 months
期刊介绍: Statistica Sinica aims to meet the needs of statisticians in a rapidly changing world. It provides a forum for the publication of innovative work of high quality in all areas of statistics, including theory, methodology and applications. The journal encourages the development and principled use of statistical methodology that is relevant for society, science and technology.
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