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Bilinear Regression Analysis : An Introduction / by Dietrich von Rosen
(Lecture Notes in Statistics. ISSN:21977186 ; 220)
Edition | 1st ed. 2018. |
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Publisher | Cham : Springer International Publishing : Imprint: Springer |
Year | 2018 |
Size | XIII, 468 p. 42 illus : online resource |
Authors | *von Rosen, Dietrich author SpringerLink (Online service) |
Subjects | LCSH:Statistics LCSH:Algebras, Linear LCSH:Biometry FREE:Statistical Theory and Methods FREE:Linear Algebra FREE:Biostatistics FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
Notes | 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 utilized. It can also be used as a text for second graduate-level courses on multivariate analysis HTTP:URL=https://doi.org/10.1007/978-3-319-78784-8 |
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E-Book | Location | Media type | Volume | Call No. | Status | Reserve | Comments | ISBN | Printed | Restriction | Designated Book | Barcode No. |
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E-Book | オンライン | 電子ブック |
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Springer eBooks | 9783319787848 |
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EB00197083 |
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