Teoria master tage 2013 2014 multivariate techniques (hardle y simar). parte del master

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Text of Teoria master tage 2013 2014 multivariate techniques (hardle y simar). parte del master

  • Wolfgang Hrdle Lopold Simar


    Second Edition


  • Wolfgang HrdleHumboldt-Universitt zu BerlinCASE - Center for Applied Statistics and EconomicsInstitut fr Statistik und konometrieSpandauer Strae 110178 Berlin, Germanye-mail: haerdle@wiwi.hu-berlin.de

    Lopold SimarUniversit Catholique LouvainInst. Statistiquevoie du Roman Payas 201348 Louvain-la-Neuve, Belgiume-mail: simar@stat.ucl.ac.be

    Cover art: Detail of Portrait of the Franciscan monk Luca Pacioli, humanist andmathematician (1445-1517)by Jacopo de Barbari, Museo di Capodimonte, Naples, Italy

    Library of Congress Control Number: 2007929787

    ISBN 978-3-540-72243-4 Springer Berlin Heidelberg New YorkISBN 978-3-540-03079-9 1st Edition Springer Berlin Heidelberg New York

    Mathematics Subject Classification (2000): 62H10, 62H12, 62H15, 62H17, 62H20,62H25, 62H30, 62F25

    This work is subject to copyright. All rights are reserved, whether the whole or part of the materialis concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,broadcasting, reproduction onmicrofilm or in any other way, and storage in data banks. Duplicationof this publication or parts thereof is permitted only under the provisions of the German CopyrightLaw of September 9, 1965, in its current version, and permission for use must always be obtainedfrom Springer. Violations are liable to prosecution under the German Copyright Law.

    Springer is a part of Springer Science+Business Media


    Springer-Verlag Berlin Heidelberg 2003, 2007

    The use of general descriptive names, registered names, trademarks, etc. in this publication doesnot imply, even in the absence of a specific statement, that such names are exempt from the relevantprotective laws and regulations and therefore free for general use.

    Production: LE-TEX Jelonek, Schmidt & Vockler GbR, LeipzigCover-design: WMX Design GmbH, Heidelberg

    SPIN 12057573 154/3180YL - 5 4 3 2 1 0 Printed on acid-free paper

  • Preface to the 2nd Edition

    The second edition of this book widens the scope of the methods and applications of AppliedMultivariate Statistical Analysis. We have introduced more up to date data sets in ourexamples. These give the text a higher degree of timeliness and add an even more appliedavour. Since multivariate statistical methods are heavily used in quantitative nance andrisk management we have put more weight on the presentation of distributions and theirdensities.

    We discuss in detail dierent families of heavy tailed distributions (Laplace, Generalized Hy-perbolic). We also devoted a section on copulae, a new concept of dependency used in thenancial risk management and credit scoring. In the chapter on computer intensive meth-ods we have added support vector machines, a new classication technique from statisticallearning theory. We apply this method to bankruptcy and rating analysis of rms. The veryimportant CART (Classication and Regression Tree) technique is also now inserted intothis chapter. We give an application to rating of companies.

    The probably most important step towards readability and user friendliness of this book isthat we have translated all Quantlets into the R and Matlab language. The algorithms can bedownloaded from the authors web sites. In the preparation of this 2nd edition, we receivedhelpful output from Anton Andriyashin, Ying Chen, Song Song and Uwe Ziegenhagen. Wewould like to thank them.

    Wolfgang Karl Hardle and Leopold Simar

    Berlin and Louvain la Neuve, June 2007

  • Preface to the 1st Edition

    Most of the observable phenomena in the empirical sciences are of a multivariate nature.In nancial studies, assets in stock markets are observed simultaneously and their jointdevelopment is analyzed to better understand general tendencies and to track indices. Inmedicine recorded observations of subjects in dierent locations are the basis of reliablediagnoses and medication. In quantitative marketing consumer preferences are collected inorder to construct models of consumer behavior. The underlying theoretical structure ofthese and many other quantitative studies of applied sciences is multivariate. This bookon Applied Multivariate Statistical Analysis presents the tools and concepts of multivariatedata analysis with a strong focus on applications.

    The aim of the book is to present multivariate data analysis in a way that is understandablefor non-mathematicians and practitioners who are confronted by statistical data analysis.This is achieved by focusing on the practical relevance and through the e-book character ofthis text. All practical examples may be recalculated and modied by the reader using astandard web browser and without reference or application of any specic software.

    The book is divided into three main parts. The rst part is devoted to graphical techniquesdescribing the distributions of the variables involved. The second part deals with multivariaterandom variables and presents from a theoretical point of view distributions, estimatorsand tests for various practical situations. The last part is on multivariate techniques andintroduces the reader to the wide selection of tools available for multivariate data analysis.All data sets are given in the appendix and are downloadable from www.md-stat.com. Thetext contains a wide variety of exercises the solutions of which are given in a separatetextbook. In addition a full set of transparencies on www.md-stat.com is provided making iteasier for an instructor to present the materials in this book. All transparencies contain hyperlinks to the statistical web service so that students and instructors alike may recompute allexamples via a standard web browser.

    The rst section on descriptive techniques is on the construction of the boxplot. Here thestandard data sets on genuine and counterfeit bank notes and on the Boston housing data areintroduced. Flury faces are shown in Section 1.5, followed by the presentation of Andrewscurves and parallel coordinate plots. Histograms, kernel densities and scatterplots completethe rst part of the book. The reader is introduced to the concept of skewness and correlationfrom a graphical point of view.

    At the beginning of the second part of the book the reader goes on a short excursion intomatrix algebra. Covariances, correlation and the linear model are introduced. This sectionis followed by the presentation of the ANOVA technique and its application to the multiplelinear model. In Chapter 4 the multivariate distributions are introduced and thereafterspecialized to the multinormal. The theory of estimation and testing ends the discussion onmultivariate random variables.

    The third and last part of this book starts with a geometric decomposition of data matrices.It is inuenced by the French school of analyse de donnees. This geometric point of viewis linked to principal components analysis in Chapter 9. An important discussion on factoranalysis follows with a variety of examples from psychology and economics. The section on

  • viii Preface

    cluster analysis deals with the various cluster techniques and leads naturally to the problemof discrimination analysis. The next chapter deals with the detection of correspondencebetween factors. The joint structure of data sets is presented in the chapter on canonicalcorrelation analysis and a practical study on prices and safety features of automobiles isgiven. Next the important topic of multidimensional scaling is introduced, followed by thetool of conjoint measurement analysis. The conjoint measurement analysis is often usedin psychology and marketing in order to measure preference orderings for certain goods.The applications in nance (Chapter 17) are numerous. We present here the CAPM modeland discuss ecient portfolio allocations. The book closes with a presentation on highlyinteractive, computationally intensive techniques.

    This book is designed for the advanced bachelor and rst year graduate student as well asfor the inexperienced data analyst who would like a tour of the various statistical tools ina multivariate data analysis workshop. The experienced reader with a bright knowledge ofalgebra will certainly skip some sections of the multivariate random variables part but willhopefully enjoy the various mathematical roots of the multivariate techniques. A graduatestudent might think that the rst part on description techniques is well known to him from histraining in introductory statistics. The mathematical and the applied parts of the book (II,III) will certainly introduce him into the rich realm of multivariate statistical data analysismodules.

    The inexperienced computer user of this e-book is slowly introduced to an interdisciplinaryway of statistical thinking and will certainly enjoy the various practical examples. Thise-book is designed as an interactive document with various links to other features. Thecomplete e-book may be downloaded from www.xplore-stat.de using the license key givenon the last page of this book. Our e-book design oers a complete PDF and HTML le withlinks to MD*Tech computing servers.

    The reader of this book may therefore use all the presented methods and data via the localXploRe Quantlet Server (XQS) without downloading or buying additional software. SuchXQ Servers may also be installed in a department or addressed freely on the web (see www.i-xplore.de for more information).

    A book of this kind would not have been possible without the help of many friends, col-leagues and students. For the technical production of the e-book we would like to thankJorg Feuerhake, Zdenek Hlavka, Torsten Kleinow, Sigbert Klinke, Heiko Lehmann, MarleneMuller. The book has been carefully read by Christian Hafner, Mia Huber, Stefan Sperlich,Axel Werwatz. We w