Multivariate least squares and its relation to other multivariate techniques

Stan Lipovetsky, Asher Tishler, W. Michael Conklin

Research output: Contribution to journalArticlepeer-review

Abstract

We consider multivariate least squares (LS) for the estimation of the connection between two data sets and show how LS is related to other multivariate techniques regularly used to analyse large data sets. LS methods are shown to be equivalent, or similar, to principal components, canonical correlations and its modifications, including a variant of the partial LS. LS approach provides a convenient unified framework for a general description and comparison of various multivariate methods, facilitates their understanding, and helps to identify their usefulness for various real-world applications. As an example we estimate and discuss the relations between data sets containing managerial variables and success measures.

Original languageEnglish
Pages (from-to)347-356
Number of pages10
JournalApplied Stochastic Models in Business and Industry
Volume18
Issue number4
DOIs
StatePublished - Oct 2002

Keywords

  • Canonical correlations
  • Inter-battery factor analysis
  • Multivariate least squares
  • Partial least squares
  • Principal components
  • Robust canonical correlations

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