Bilinear Regression Analysis

An Introduction de

Éditeur :

Springer


Collection :

Lecture Notes in Statistics

Paru le : 2018-08-02

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Description
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.



Pages
468 pages
Collection
Lecture Notes in Statistics
Parution
2018-08-02
Marque
Springer
EAN papier
9783319787824
EAN PDF
9783319787848

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
46
Taille du fichier
5683 Ko
Prix
79,11 €
EAN EPUB
9783319787848

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
46
Taille du fichier
33485 Ko
Prix
79,11 €