Advertisement

Latent Variable Models for Blind Source Separation

  • Alan Julian Izenman
Part of the Springer Texts in Statistics book series (STS)

Abstract

Correspondence analysis is an exploratory multivariate technique for simultaneously displaying scores representing the row categories and column categories of a two-way contingency table as the coordinates of points in a low-dimensional (two- or possibly three-dimensional) vector space. The objective is to clarify the relationship between the row and column variates of the table and to discover a low-dimensional explanation for possible deviations from independence of those variates. The methodology has its own nomenclature, and its approach is decidedly geometric, especially for interpreting the resulting graphical displays.

Keywords

Independent Component Analysis Independent Component Analysis Blind Source Separation Latent Variable Model Projection Pursuit 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Alan Julian Izenman
    • 1
  1. 1.Department of StatisticsTemple UniversityPhiladelphiaUSA

Personalised recommendations