Applied Multidimensional Scaling and Unfolding

This book introduces multidimensional scaling (MDS) and unfolding as data analysis techniques for applied researchers. MDS is used for the analysis of proximity data on a set of objects, representing the data as distances between points in a geometric spa

  • PDF / 5,173,668 Bytes
  • 128 Pages / 439.37 x 666.142 pts Page_size
  • 12 Downloads / 181 Views

DOWNLOAD

REPORT


Ingwer Borg Patrick J. F. Groenen Patrick Mair

Applied Multidimensional Scaling and Unfolding Second Edition

SpringerBriefs in Statistics

SpringerBriefs present concise summaries of cutting-edge research and practical applications across a wide spectrum of fields. Featuring compact volumes of 50 to 125 pages, the series covers a range of content from professional to academic. Typical topics might include: • A timely report of state-of-the art analytical techniques • A bridge between new research results, as published in journal articles, and a contextual literature review • A snapshot of a hot or emerging topic • An in-depth case study or clinical example • A presentation of core concepts that students must understand in order to make independent contributions SpringerBriefs in Statistics showcase emerging theory, empirical research, and practical application in Statistics from a global author community. SpringerBriefs are characterized by fast, global electronic dissemination, standard publishing contracts, standardized manuscript preparation and formatting guidelines, and expedited production schedules.

More information about this series at http://www.springer.com/series/8921

Ingwer Borg Patrick J. F. Groenen Patrick Mair •

Applied Multidimensional Scaling and Unfolding Second Edition

123

Ingwer Borg Westfälische Wilhelms-Universität Münster Germany

Patrick Mair Department of Psychology Harvard University Cambridge, MA USA

Patrick J. F. Groenen Econometric Institute Erasmus University Rotterdam Rotterdam The Netherlands

Additional material to this book can be downloaded from http://extras.springer.com. ISSN 2191-544X ISSN 2191-5458 (electronic) SpringerBriefs in Statistics ISBN 978-3-319-73470-5 ISBN 978-3-319-73471-2 (eBook) https://doi.org/10.1007/978-3-319-73471-2 Library of Congress Control Number: 2018934861 Mathematics Subject Classification (2010): 91C15 © The Author(s) 2013, 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 neutra