Bilinear Regression Analysis An Introduction
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
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Dietrich von Rosen
Bilinear Regression Analysis An Introduction
Lecture Notes in Statistics Edited by P. Bickel, P. Diggle, S.E. Fienberg, U. Gather, S. Zeger
220
More information about this series at http://www.springer.com/series/694
Dietrich von Rosen
Bilinear Regression Analysis An Introduction
123
Dietrich von Rosen Department of Energy and Technology Swedish University of Agricultural Sciences Uppsala, Sweden
ISSN 0930-0325 ISSN 2197-7186 (electronic) Lecture Notes in Statistics ISBN 978-3-319-78782-4 ISBN 978-3-319-78784-8 (eBook) https://doi.org/10.1007/978-3-319-78784-8 Library of Congress Control Number: 2018943157 Mathematics Subject Classification (2010): 62H12, 62H15, 62H99, 62J20, 15A69, 15A03, 15A63 © Springer International Publishing AG, part of Springer Nature 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by the registered company Springer International Publishing AG part of Springer Nature The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
To Tatjana, Alexander, Evelina, Michael, Philip, Sophie
Preface
This book can be regarded as a textbook on bilinear regression analysis which could be used for a second course on classical multivariate analysis. The first course in such a series would deal with multivariate linear models, focusing, for example, on the estimation of parameters and the testing of hypotheses in such models. However, the book definitely does not require any knowledge of PCA, PCR, PLS, factor analysis, cluster analysis, multidimensional scaling, etc., since it does not treat any of these methods or any related methods. The most important prerequisite is some knowledge of linear models (univariate and/or multivariate models), and some knowledge of the basics of linear algebra would be helpful. The book has been written
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