Multivariate Statistics:: Exercises and Solutions

by Wolfgang Karl Härdle, Zdenek Hlávka

Overview

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 thatareentirelydifferentfromtheanalysisofone-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 proficient, 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.

Product Details

ISBN-13:	9780387707846
Publisher:	Springer New York
Publication date:	07/27/2007
Edition description:	2007
Pages:	368
Product dimensions:	6.10(w) x 9.25(h) x 0.04(d)

About the Author

Wolfgang Karl Härdle is the Ladislaus von Bortkiewicz Professor of Statistics at the Humboldt-Universität zu Berlin and director of C.A.S.E. (Center for Applied Statistics and Economics), director of the CRC-649 (Collaborative Research Center) “Economic Risk” and director of the IRTG 1792 “High Dimensional Non-stationary Time Series”. He teaches quantitative finance and semi-parametric statistics. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected member of the ISI (International Statistical Institute) and advisor to the Guanghua School of Management, Peking University, and senior fellow of Sim Kee Boon Institute of Financial Economics at the Singapore Management University.

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.

Table of Contents

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.

Editorial Reviews

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)

From the Publisher