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Bilinear Regression Analysis: An Introduction 2018 Edition
Contributor(s): Von Rosen, Dietrich (Author)

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 ISBN: 3319787829     ISBN-13: 9783319787824
Publisher: Springer
OUR PRICE: $80.74  

Binding Type: Paperback - See All Available Formats & Editions
Published: August 2018
Qty:

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Additional Information
BISAC Categories:
- Mathematics | Probability & Statistics - General
- Mathematics | Algebra - Linear
- Medical | Biostatistics
Dewey: 512.5
Series: Lecture Notes in Statistics
Physical Information: 0.97" H x 6.14" W x 9.21" L (1.48 lbs) 468 pages
 
Descriptions, Reviews, Etc.
Publisher 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.
 
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