Overview
This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph.D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.
Full Product Details
Author: Dietrich von Rosen
Publisher: Springer International Publishing AG
Imprint: Springer International Publishing AG
Edition: 2018 ed.
Volume: 220
Weight: 0.735kg
ISBN: 9783319787824
ISBN 10: 3319787829
Pages: 468
Publication Date: 03 August 2018
Audience:
Professional and scholarly
,
College/higher education
,
Professional & Vocational
,
Postgraduate, Research & Scholarly
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
The present book offers a complete presentation of the statistical techniques concerning bilinear regression analysis. ... A special mention goes to the bibliography that accompanies each chapter. Far from being a simple list of papers containing the results recalled in the text, it is a real history of statistics, where the early ideas of bilinear regression are highlighted. (Fabio Rapallo, zbMATH 1398.62003, 2018)
Author Information
Dietrich von Rosen is a professor at the Department of Energy and Technology at the Swedish University of Agricultural Sciences. He graduated in mathematical statistics from Stockholm University, Sweden. His main research interest is multivariate analysis and its extensions, including repeated measurements analysis and high-dimensional analysis. He has published more than 100 papers, the majority of which are within the above areas, as well as a book on advanced multivariate statistics and matrices in collaboration with Tõnu Kollo, professor of mathematical statistics at the University of Tartu, Estonia.
