Linear methods in multimode data analysis for decision making

S. Lipovetsky*, A. Tishler

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This paper presents and analyses several methods for the evaluation of information given in the form of many-way matrices. These methods are based on the least squares approximation of a matrix by a many-vector product which can be represented as a nonlinear eigenvector problem. Using real data about university choice by high school graduates in Israel, we develop and compare the following three families of methods: parallel proportional profiles, various types of methods based on the use of cyclic matrices (canonical correlations, principal components, and planes' approximation), and minimization of relative deviations.

Original languageEnglish
Pages (from-to)169-183
Number of pages15
JournalComputers and Operations Research
Issue number2
StatePublished - Feb 1994


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