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Correspondence analysis and the Freeman-Tukey statistic: A study of archaeological data

机译:函授分析与弗里曼 - Tukey统计:考古数据的研究

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摘要

Traditionally, simple correspondence analysis is performed by decomposing a matrix of standardised residuals using singular value decomposition where the sum-of-squares of these residuals gives Pearson's chi-squared statistic. Such residuals, which are treated as being asymptotically normally distributed, arise by assuming that the cell frequencies are Poisson random variables so that their mean and variance are the same. However, studies in the past reveal that this is not the case and that the cell frequencies are prone to overdispersion. There are a growing number of remedies that have been proposed in the statistics, and allied, literature. One such remedy, and the focus of this paper, is to stabilise the variance using the Freeman-Tukey transformation. Therefore, the properties that stem from performing correspondence analysis will be examined by decomposing the Freeman-Tukey residuals of a two-way contingency table. The application of this strategy shall be made by studying one large, and sparse, set of archaeological data. Crown Copyright (C) 2018 Published by Elsevier B.V. All rights reserved.
机译:传统上,通过使用奇异值分解来分解标准化残留的矩阵来执行简单的对应分析,其中这些残差的平方和使Pearson的Chi Squared统计数据。通过假设细胞频率是泊松随机变量,因此将被视为渐近地分布的这种残留物是渐近的。然而,过去的研究表明,这不是这种情况,并且细胞频率易于过度分解。在统计数据中提出了越来越多的补救措施,以及盟军的文献。一种这样的补救措施和本文的重点是使用Freeman-Tukey转换稳定方差。因此,将通过分解双向差符表表的弗雷曼-Tukey剩余物来检查源代理分析的性质。该策略的应用应通过研究一个大,稀疏,稀疏的考古数据进行。 Crown版权(c)2018由elestvier b.v出版。保留所有权利。

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