Multivariate Statistics:: Exercises and Solutions

ISBN-13: 9780387707846 / Angielski / Miękka / 2007 / 368 str.

Wolfgang Hardle; Zdenek Hlavka

Opis

There can be no question, my dear Watson, of the value of exercise before breakfast. Sherlock Holmes in "The Adventure of Black Peter" The statistical analysis of multivariate data requires a variety of techniques thatareentirelydi?erentfromtheanalysisofone-dimensionaldata.Thestudy of the joint distribution of many variables in high dimensions involves matrix techniques that are not part of standard curricula. The same is true for tra- formations and computer-intensive techniques, such as projection pursuit. The purpose of this book is to provide a set of exercises and solutions to help the student become familiar with the techniques necessary to analyze high-dimensional data. It is our belief that learning to apply multivariate statistics is like studying the elements of a criminological case. To become pro?cient, students must not simply follow a standardized procedure, they must compose with creativity the parts of the puzzle in order to see the big picture. We therefore refer to Sherlock Holmes and Dr. Watson citations as typical descriptors of the analysis. Puerile as such an exercise may seem, it sharpens the faculties of observation, and teaches one where to look and what to look for.

Recenzje

In general, I find this book particularly instructive, by discussing various techniques and analytical tools via exercises with rigorous solutions. The computer codes for computer-based exercises are available in R or XploRe languages through the Springer link web pages and from the authors home pages. The web links also provide access to real datasets used in the book. This is a very useful exercise book for students and instructors as well as for nonexperts using in applied multivariate data analysis. There has been large demand for techniques to handle and analyze high-dimensional data. In this regard, the book would be a good reference for researchers and students working in the theory or applications of multivariate statistical analysis. (Journal of the American Statistical Association, Dec. 2009, Vol. 104, No. 488)

Spis treści

Descriptive Techniques.- Comparison of Batches.- Multivariate Random Variables.- A Short Excursion into Matrix Algebra.- Moving to Higher Dimensions.- Multivariate Distributions.- Theory of the Multinormal.- Theory of Estimation.- Hypothesis Testing.- Multivariate Techniques.- Decomposition of Data Matrices by Factors.- Principal Component Analysis.- Factor Analysis.- Cluster Analysis.- Discriminant Analysis.- Correspondence Analysis.- Canonical Correlation Analysis.- Multidimensional Scaling.- Conjoint Measurement Analysis.- Applications in Finance.- Highly Interactive, Computationally Intensive Techniques.

O autorze

Zdenek Hlávka studied mathematics at the Charles University in Prague and biostatistics at Limburgs Universitair Centrum in Diepenbeek. Later he held a position at Humboldt-Universität zu Berlin before he became a member of the Department of Probability and Mathematical Statistics at Charles University in Prague. Wolfgang Härdle is a professor of statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. the Centre for Applied Statistics and Economics. He teaches quantitative finance and semiparametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected ISI member and advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.

Blurb

The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether 234 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R or XploRe languages. The corresponding libraries are downloadable from the Springer link web pages and from the author’s home pages.

Wolfgang Härdle is Professor of Statistics at Humboldt-Universität zu Berlin. He studied mathematics, computer science and physics at the University of Karlsruhe and received his Dr.rer.nat. at the University of Heidelberg. Later he had positions at Frankfurt and Bonn before he became professeur ordinaire at Université Catholique de Louvain. His current research topic is modelling of implied volatilities and the quantitative analysis of financial markets.

Zdenek Hlávka studied mathematics at the Charles University in Prague and biostatistics at Limburgs Universitair Centrum in Diepenbeek. Later he held a position at Humboldt-Universität zu Berlin before he became a member of the Department of Probability and Mathematical Statistics at Charles University in Prague.