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New Perspectives in Partial Least Squares and Related Methods

  • Conference proceedings
  • © 2013

Overview

  • Communications from recognized leaders in the fields, who were invited speakers at the meeting
  • Important applications in hot domains such as genomics, brain imaging, sensory analysis
  • Integrates recent theoretical and methodological advances?
  • Covers both PLS regression and PLS-path modeling
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 56)

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Table of contents (22 papers)

  1. Keynotes

  2. Large Datasets and Genomics

  3. Brain Imaging

  4. Multiblock Data Modeling

Keywords

About this book

New Perspectives in Partial Least Squares and Related Methods shares original, peer-reviewed research from presentations during the 2012 partial least squares methods meeting (PLS 2012). This was the 7th meeting in the series of PLS conferences and the first to take place in the USA. PLS is an abbreviation for Partial Least Squares and is also sometimes expanded as projection to latent structures. This is an approach for modeling relations between data matrices of different types of variables measured on the same set of objects. The twenty-two papers in this volume, which include three invited contributions from our keynote speakers, provide a comprehensive overview of the current state of the most advanced research related to PLS and related methods. Prominent scientists from around the world took part in PLS 2012 and their contributions covered the multiple dimensions of the partial least squares-based methods. These exciting theoretical developments ranged from partial least squares regression and correlation, component based path modeling to regularized regression and subspace visualization. In following the tradition of the six previous PLS meetings, these contributions also included a large variety of PLS approaches such as PLS metamodels, variable selection, sparse PLS regression, distance based PLS, significance vs. reliability, and non-linear PLS. Finally, these contributions applied PLS methods to data originating from the traditional econometric/economic data to genomics data, brain images, information systems, epidemiology, and chemical spectroscopy. Such a broad and comprehensive volume will also encourage new uses of PLS models in work by researchers and students in many fields. 

Editors and Affiliations

  • School of Behavioral & Brain Sciences, The University of Texas at Dallas, Richardson, USA

    Herve Abdi

  • Department of Decision and Information Systems, University of Houston, Houston, USA

    Wynne W. Chin

  • ESSEC Business School of Paris, Cergy-Pontoise Cedex, France

    Vincenzo Esposito Vinzi

  • CNAM, Paris, USA

    Giorgio Russolillo

  • Rouen Business School, Rouen, France

    Laura Trinchera

About the editors

The five editors of this volume present work from the 2012 partial least squares methods meeting (PLS 2012) in Houston, Texas.

Bibliographic Information

  • Book Title: New Perspectives in Partial Least Squares and Related Methods

  • Editors: Herve Abdi, Wynne W. Chin, Vincenzo Esposito Vinzi, Giorgio Russolillo, Laura Trinchera

  • Series Title: Springer Proceedings in Mathematics & Statistics

  • DOI: https://doi.org/10.1007/978-1-4614-8283-3

  • Publisher: Springer New York, NY

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer Science+Business Media New York 2013

  • Hardcover ISBN: 978-1-4614-8282-6Published: 17 October 2013

  • Softcover ISBN: 978-1-4939-4685-3Published: 23 August 2016

  • eBook ISBN: 978-1-4614-8283-3Published: 17 October 2013

  • Series ISSN: 2194-1009

  • Series E-ISSN: 2194-1017

  • Edition Number: 1

  • Number of Pages: XXIII, 344

  • Number of Illustrations: 47 b/w illustrations, 49 illustrations in colour

  • Topics: Statistical Theory and Methods, Statistics, general

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