Ebook: Multivariate Statistics: Exercises and Solutions

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.

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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 H?rdle is Professor of Statistics at Humboldt-Universit?t 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 Universit? Catholique de Louvain. His current research topic is modelling of implied volatilities and the quantitative analysis of financial markets.

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

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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 H?rdle is Professor of Statistics at Humboldt-Universit?t 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 Universit? Catholique de Louvain. His current research topic is modelling of implied volatilities and the quantitative analysis of financial markets.

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

Content:
Front Matter....Pages i-xxv
Front Matter....Pages 14-14
Comparison of Batches....Pages 15-30
Front Matter....Pages 32-32
A Short Excursion into Matrix Algebra....Pages 33-37
Moving to Higher Dimensions....Pages 39-54
Multivariate Distributions....Pages 55-80
Theory of the Multinormal....Pages 81-97
Theory of Estimation....Pages 99-110
Hypothesis Testing....Pages 111-144
Front Matter....Pages 146-146
Decomposition of Data Matrices by Factors....Pages 147-162
Principal Component Analysis....Pages 163-183
Factor Analysis....Pages 185-204
Cluster Analysis....Pages 205-225
Discriminant Analysis....Pages 227-240
Correspondence Analysis....Pages 241-262
Canonical Correlation Analysis....Pages 263-269
Multidimensional Scaling....Pages 271-281
Conjoint Measurement Analysis....Pages 283-290
Applications in Finance....Pages 291-299
Highly Interactive, Computationally Intensive Techniques....Pages 301-323
Back Matter....Pages 325-368

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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 H?rdle is Professor of Statistics at Humboldt-Universit?t 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 Universit? Catholique de Louvain. His current research topic is modelling of implied volatilities and the quantitative analysis of financial markets.

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

Content:
Front Matter....Pages i-xxv
Front Matter....Pages 14-14
Comparison of Batches....Pages 15-30
Front Matter....Pages 32-32
A Short Excursion into Matrix Algebra....Pages 33-37
Moving to Higher Dimensions....Pages 39-54
Multivariate Distributions....Pages 55-80
Theory of the Multinormal....Pages 81-97
Theory of Estimation....Pages 99-110
Hypothesis Testing....Pages 111-144
Front Matter....Pages 146-146
Decomposition of Data Matrices by Factors....Pages 147-162
Principal Component Analysis....Pages 163-183
Factor Analysis....Pages 185-204
Cluster Analysis....Pages 205-225
Discriminant Analysis....Pages 227-240
Correspondence Analysis....Pages 241-262
Canonical Correlation Analysis....Pages 263-269
Multidimensional Scaling....Pages 271-281
Conjoint Measurement Analysis....Pages 283-290
Applications in Finance....Pages 291-299
Highly Interactive, Computationally Intensive Techniques....Pages 301-323
Back Matter....Pages 325-368
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