Multivariate Statistics
Springer Berlin (Verlag)
978-3-642-36004-6 (ISBN)
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 data sets are included in the library SMSdata that may be downloaded via the quantlet download center www.quantlet.org. Data sets are available also via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.
Wolfgang Karl Härdle is a Professor of Statistics at the Humboldt-Universität zu Berlin and the Director of CASE the Centre for Applied Statistics and Economics. He teaches quantitative finance and semi-parametric statistical methods. His research focuses on dynamic factor models, multivariate statistics in finance and computational statistics. He is an elected member of the ISI and an advisor to the Guanghua School of Management, Peking University and to National Central University, Taiwan.
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.
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 book basically contains a large number of exercises along with their solutions. ... This book is a good source for researchers in the area of multivariate data analysis. It is also a good supplement to an advanced course on the subject. ... this book takes a somewhat unique and different approach than a traditional textbook where one usually sees a topic covered in depth followed by a number of examples/exercises." (Morteza Marzjarani, Technometrics, Vol. 58 (4), April, 2016)
| Erscheint lt. Verlag | 12.6.2015 |
|---|---|
| Zusatzinfo | XXIV, 362 p. 123 illus., 30 illus. in color. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 595 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Statistik |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Data Analysis • Factor Analysis • factor model • high dimensional data analysis • multivariate distribution • Multivariate Statistics • principal component • quantlets • regression models • Statistik |
| ISBN-10 | 3-642-36004-1 / 3642360041 |
| ISBN-13 | 978-3-642-36004-6 / 9783642360046 |
| Zustand | Neuware |
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