Multivariate statistics : exercises and solutions / Wolfgang Karl Härdle and Zdeněk Hlávka.

By: Härdle,Wolfgang Contributor(s): Hlávka, Zdeněk Material type: Text

TextLanguage: English Publication details: Heidelberg : Springer, 2015. Edition: 2nd edDescription: xxiv, 362 p. : ill. ; 24 cmISBN: 9783642360046; 3642360041Subject(s): Multivariate analysis | Statistical Theory and Methods | Computational Mathematics and Numerical AnalysisDDC classification: 519.535 Online resources: WorldCat details | Ebook Fulltext

Contents:

TOC Part I Descriptive Techniques: Comparison of Batches -- Part II Multivariate Random Variables: A Short Excursion into Matrix Algebra -- Moving to Higher -- Multivariate -- Theory of the Multinormal -- Theory of Estimation -- Part III Multivariate Techniques: Regression Models -- Variable Selection -- 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 -- Data Sets -- References -- Index.

Summary: 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 more than 250 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 language. All R codes and data sets may be downloaded via the quantlet download center www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.

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Item type	Current library	Collection	Call number	Copy number	Status	Barcode
E-Book	EWU Library E-book	Non-fiction	519.535 HAM 2015 (Browse shelf(Opens below))		Not for loan
Text	EWU Library Reserve Section	Non-fiction	519.535 HAM 2015 (Browse shelf(Opens below))	C-1	Not For Loan	27308
Text	EWU Library Circulation Section	Non-fiction	519.535 HAM 2015 (Browse shelf(Opens below))	C-2	Available	27309

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Previous	519.535 BYS Structural equation modeling with AMOS :	519.535 EVI 2011 An introduction to applied multivariate analysis with R /	519.535 FIA 2007 The analysis of cross-classified categorical data /	519.535 HAM 2015 Multivariate statistics :	519.535 HID 2008 Design and analysis of experiments.	519.535 HID 2008 Design and analysis of experiments.	519.535 HID 2008 Design and analysis of experiments.	Next

Includes Bibliographical References and Index.

TOC Part I Descriptive Techniques: Comparison of Batches --
Part II Multivariate Random Variables: A Short Excursion into Matrix Algebra --
Moving to Higher --
Multivariate --
Theory of the Multinormal --
Theory of Estimation --
Part III Multivariate Techniques: Regression Models --
Variable Selection --
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 --
Data Sets --
References --
Index.

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 more than 250 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 language. All R codes and data sets may be downloaded via the quantlet download center www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.

Sagar Shahanawaz

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