Overview
- Integrates theoretical and methodological advances from recognized leaders in the field, including the conference's invited speakers
- Important applications in domains such as genomics, brain imaging, sensory analysis, marketing, psychometrics and information systems
- Covers PLS regression, PLS path modeling and developments that go beyond PLS specific methods, extending to other component-based and multi-block or multi-way methods
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Proceedings in Mathematics & Statistics (PROMS, volume 173)
Included in the following conference series:
Conference proceedings info: PLS 2014.
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Table of contents (22 papers)
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Front Matter
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Keynotes
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Front Matter
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New Developments in Genomics and Brain Imaging
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Front Matter
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New and Alternative Methods for Multitable and Path Analysis
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Front Matter
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Advances in Partial Least Square Regression
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Front Matter
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Other volumes
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The Multiple Facets of Partial Least Squares and Related Methods
Keywords
About this book
Editors and Affiliations
About the editors
Hervé Abdi—a former Fulbright scholar and resident of the Paris Institute for Advanced Studies—is professor of cognitive neuroscience at the University of Texas at Dallas. His recent research interests focus on the development of analytical and statistical tools for the analysis of very large data sets as generated, for example, by brain imaging, genetic, genomic, and sensory science research. In addition to Partial Least Squares (PLS) models, he is also particularly interested in variable selection and in multi-modal, multi-way, and multi-block methods. He is the author of more than 250 publications (including 12 books) in these domains.
Vincenzo Esposito Vinzi—a former President of the International Society for Business and Industrial Statistics (ISBIS)—is professor of statistics and Dean of the Faculty at the ESSEC Business School in Paris and Singapore. His research interests focus mainly on methodological developments in multivariate statistics, namelyfactorial methods, structural equation modeling, PLS regression, and predictive path modeling that are relevant to various applications in business and industry, sensory data, social surveys, and the measurement of customer satisfaction for commodities and public services.
Giorgio Russolillo is associate professor of statistics at the Conservatoire National des Arts et Métiers (CNAM) of Paris where he is a member of the CEDRIC research group. His research interests involve multivariate data analysis models and methods applied to social and life sciences. Much of his current research focuses on PLS algorithms.
Gilbert Saporta—a former president of the International Association for Statistical Computing—is emeritus professor of applied statistics at the Conservatoire National des Arts et Métiers (CNAM) of Paris. His research interests are in exploratory multivariate analysis: functional data analysis including functional PLS, sparse methods, and supervised classification.
Laura Trinchera is assistant professor of computational statistics at the NEOMA business school (Rouen Campus, France). Her research interests cover multivariate analyses, structural equation models (SEM), PLS methods. She is also interested in variable selection in regression models.
Bibliographic Information
Book Title: The Multiple Facets of Partial Least Squares and Related Methods
Book Subtitle: PLS, Paris, France, 2014
Editors: Hervé Abdi, Vincenzo Esposito Vinzi, Giorgio Russolillo, Gilbert Saporta, Laura Trinchera
Series Title: Springer Proceedings in Mathematics & Statistics
DOI: https://doi.org/10.1007/978-3-319-40643-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-40641-1Published: 14 October 2016
Softcover ISBN: 978-3-319-82144-3Published: 16 June 2018
eBook ISBN: 978-3-319-40643-5Published: 13 October 2016
Series ISSN: 2194-1009
Series E-ISSN: 2194-1017
Edition Number: 1
Number of Pages: XIV, 316
Number of Illustrations: 29 b/w illustrations, 39 illustrations in colour
Topics: Statistical Theory and Methods, Mathematical Models of Cognitive Processes and Neural Networks, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences