Authors:
- Integrates multivariate data analysis with Riemannian geometry
- Provides a unified treatment of several MDA techniques
- Incorporates new tools and technology into current theory of MDA
- Includes Manpot codes which can be directly used to solve a number of problems or be used as templates to create new codes
Part of the book series: Springer Series in the Data Sciences (SSDS)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (11 chapters)
-
Front Matter
-
Back Matter
About this book
Authors and Affiliations
-
Dept of Mathematics and Statistics, Open University, Milton Keynes, UK
Nickolay Trendafilov
-
Dept of Human & Social Sciences, Univ degli Studi di Napoli "L'Orientale, Naples, Italy
Michele Gallo
About the authors
Michele Gallo is Professor in the Department of Human and Social Sciences at the University of Naples – L’Orientale. He received his PhD degree in Total Quality Management from the University of Naples – Federico II, in 2000. His current research interest is in Multivariate Data Analysis, Compositional and Ordinal Data, Rasch Analysis. He has published more than 90 research articles. He is Associate-Editor of the journal Computational Statistics.
Bibliographic Information
Book Title: Multivariate Data Analysis on Matrix Manifolds
Book Subtitle: (with Manopt)
Authors: Nickolay Trendafilov, Michele Gallo
Series Title: Springer Series in the Data Sciences
DOI: https://doi.org/10.1007/978-3-030-76974-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-76973-4Published: 16 September 2021
Softcover ISBN: 978-3-030-76976-5Published: 16 September 2022
eBook ISBN: 978-3-030-76974-1Published: 15 September 2021
Series ISSN: 2365-5674
Series E-ISSN: 2365-5682
Edition Number: 1
Number of Pages: XX, 450
Number of Illustrations: 1 b/w illustrations, 5 illustrations in colour
Topics: Computational Mathematics and Numerical Analysis, Global Analysis and Analysis on Manifolds, Math Applications in Computer Science