Stegeman Alwin, Berge Jos M F Ten, Lathauwer Lieven De
University of Groningen, Groningen.
Heijmans Institute of Psychological Research, University of Groningen, Grote Kruisstraat 2/1, 9712 TS, Groningen, The Netherlands.
Psychometrika. 2006 Jun;71(2):219-229. doi: 10.1007/11336-006-1278-2. Epub 2017 Feb 11.
A key feature of the analysis of three-way arrays by Candecomp/Parafac is the essential uniqueness of the trilinear decomposition. We examine the uniqueness of the Candecomp/Parafac and Indscal decompositions. In the latter, the array to be decomposed has symmetric slices. We consider the case where two component matrices are randomly sampled from a continuous distribution, and the third component matrix has full column rank. In this context, we obtain almost sure sufficient uniqueness conditions for the Candecomp/Parafac and Indscal models separately, involving only the order of the three-way array and the number of components in the decomposition. Both uniqueness conditions are closer to necessity than the classical uniqueness condition by Kruskal.
通过Candecomp/Parafac对三维数组进行分析的一个关键特征是三线性分解的基本唯一性。我们研究了Candecomp/Parafac分解和Indscal分解的唯一性。在后者中,待分解的数组具有对称切片。我们考虑从连续分布中随机采样两个分量矩阵,且第三个分量矩阵具有满列秩的情况。在此背景下,我们分别得到了Candecomp/Parafac模型和Indscal模型几乎必然的充分唯一性条件,这些条件仅涉及三维数组的阶数和分解中的分量数量。与Kruskal的经典唯一性条件相比,这两个唯一性条件都更接近必要性条件。