Bilinear Regression Analysis : An Introduction. 1st ed. 2018

種類:

電子ブック

責任表示:

by Dietrich von Rosen

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2018

著者名:

• von Rosen, Dietrich.
• SpringerLink (Online service)

シリーズ名:

Lecture Notes in Statistics ; 220

ISBN:

9783319787848 [3319787845]    

注記:

Preface -- Introduction -- The Basic Ideas of Obtaining MLEs: A Known Dispersion -- The Basic Ideas of Obtaining MLEs: Unknown Dispersion -- Basic Properties of Estimators -- Density Approximations -- Residuals -- Testing Hypotheses -- Influential Observations -- Appendices -- Indices.
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 utili

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