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具有偏移项的三元成分模型拟合的性质与算法

Properties of and Algorithms for Fitting Three-Way Component Models with Offset Terms.

作者信息

Kiers Henk A L

机构信息

University of Groningen, Groningen.

Heymans Institute, University of Groningen, Grote Kruisstraat 2/1, 9712 TS, Groningen, The Netherlands.

出版信息

Psychometrika. 2006 Jun;71(2):231-256. doi: 10.1007/s11336-001-0953-x. Epub 2017 Feb 11.

Abstract

Prior to a three-way component analysis of a three-way data set, it is customary to preprocess the data by centering and/or rescaling them. Harshman and Lundy (1984) considered that three-way data actually consist of a three-way model part, which in fact pertains to ratio scale measurements, as well as additive "offset" terms that turn the ratio scale measurements into interval scale measurements. They mentioned that such offset terms might be estimated by incorporating additional components in the model, but discarded this idea in favor of an approach to remove such terms from the model by means of centering. Then estimates for the three-way component model parameters are obtained by analyzing the centered data. In the present paper, the possibility of actually estimating the offset terms is taken up again. First, it is mentioned in which cases such offset terms can be estimated uniquely. Next, procedures are offered for estimating model parameters and offset parameters simultaneously, as well as successively (i.e., providing offset term estimates after the three-way model parameters have been estimated in the traditional way on the basis of the centered data). These procedures are provided for both the CANDECOMP/PARAFAC model and the Tucker3 model extended with offset terms. The successive and the simultaneous approaches for estimating model and offset parameters have been compared on the basis of simulated data. It was found that both procedures perform well when the fitted model captures at least all offset terms actually underlying the data. The simultaneous procedures performed slightly better than the successive procedures. If fewer offset terms are fitted than there are underlying the model, the results are considerably poorer, but in these cases the successive procedures performed better than the simultaneous ones. All in all, it can be concluded that the traditional approach for estimating model parameters can hardly be improved upon, and that offset terms can sufficiently well be estimated by the proposed successive approach, which is a simple extension of the traditional approach.

摘要

在对一个三向数据集进行三向成分分析之前,通常会通过对数据进行中心化和/或重新缩放来进行预处理。哈什曼和伦迪(1984年)认为,三向数据实际上由一个三向模型部分组成,该部分实际上属于比率尺度测量,以及将比率尺度测量转换为区间尺度测量的加法“偏移”项。他们提到,可以通过在模型中纳入额外的成分来估计此类偏移项,但放弃了这个想法,转而采用一种通过中心化从模型中去除此类项的方法。然后,通过分析中心化后的数据来获得三向成分模型参数的估计值。在本文中,再次探讨了实际估计偏移项的可能性。首先,提到了在哪些情况下可以唯一地估计此类偏移项。接下来,提供了同时估计模型参数和偏移参数以及相继估计(即,在基于中心化数据以传统方式估计三向模型参数之后提供偏移项估计)的程序。这些程序适用于CANDECOMP/PARAFAC模型以及扩展了偏移项的Tucker3模型。基于模拟数据对估计模型和偏移参数的相继方法和同时方法进行了比较。结果发现,当拟合模型至少捕捉到数据实际潜在的所有偏移项时,这两种程序都表现良好。同时程序的表现略优于相继程序。如果拟合的偏移项少于模型潜在的偏移项,结果会相当差,但在这些情况下,相继程序的表现优于同时程序。总而言之,可以得出结论,估计模型参数的传统方法几乎无法改进,并且通过所提出的相继方法可以很好地估计偏移项,该方法是传统方法的简单扩展。

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