Literature DB >> 19897815

The LMPCA program: a graphical user interface for fitting the linked-mode PARAFAC-PCA model to coupled real-valued data.

Tom F Wilderjans1, Eva Ceulemans, Henk A L Kiers, Kristof Meers.   

Abstract

In behavioral research, PARAFAC analysis, a three-mode generalization of standard principal component analysis (PCA), is often used to disclose the structure of three-way three-mode data. To get insight into the underlying mechanisms, one often wants to relate the component matrices resulting from such a PARAFAC analysis to external (two-way two-mode) information, regarding one of the modes of the three-way data. To this end, linked-mode PARAFAC-PCA analysis can be used, in which the three-way and the two-way data set, which have one mode in common, are simultaneously analyzed. More specifically, a PARAFAC and a PCA model are fitted to the three-way and the two-way data, respectively, restricting the component matrix for the common mode to be equal in both models. Until now, however, no software program has been publicly available to perform such an analysis. Therefore, in this article, the LMPCA program, a free and easy-to-use MATLAB graphical user interface, is presented to perform a linked-mode PARAFAC-PCA analysis. The LMPCA software can be obtained from the authors at http://ppw.kuleuven.be/okp/software/LMPCA. For users who do not have access to MATLAB, a stand-alone version is provided.

Mesh:

Year:  2009        PMID: 19897815     DOI: 10.3758/BRM.41.4.1073

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  2 in total

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Authors:  Xiao-Feng Gong; Ke Wang; Qiu-Hua Lin; Zhi-Wen Liu; You-Gen Xu
Journal:  Sensors (Basel)       Date:  2012-03-08       Impact factor: 3.576

2.  Structure-revealing data fusion.

Authors:  Evrim Acar; Evangelos E Papalexakis; Gözde Gürdeniz; Morten A Rasmussen; Anders J Lawaetz; Mathias Nilsson; Rasmus Bro
Journal:  BMC Bioinformatics       Date:  2014-07-12       Impact factor: 3.169

  2 in total

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