Multivariate Nonparametric Regression and Visualization

With R and Applications to Finance

Nonfiction, Computers, Programming, Programming Languages, Visual BASIC, Science & Nature, Mathematics, Statistics
Cover of the book Multivariate Nonparametric Regression and Visualization by Jussi Sakari Klemelä, Wiley
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Author: Jussi Sakari Klemelä ISBN: 9781118593509
Publisher: Wiley Publication: May 5, 2014
Imprint: Wiley-Interscience Language: English
Author: Jussi Sakari Klemelä
ISBN: 9781118593509
Publisher: Wiley
Publication: May 5, 2014
Imprint: Wiley-Interscience
Language: English

A modern approach to statistical learning and its applications through visualization methods

With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generating mechanisms, the book begins with an overview of classification and regression.

The book then introduces and examines various tested and proven visualization techniques for learning samples and functions. Multivariate Nonparametric Regression and Visualization identifies risk management, portfolio selection, and option pricing as the main areas in which statistical methods may be implemented in quantitative finance. The book provides coverage of key statistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, and nearest neighbor methods. Exploring the additional applications of nonparametric and semiparametric methods, Multivariate Nonparametric Regression and Visualization features:

  • An extensive appendix with R-package training material to encourage duplication and modification of the presented computations and research
  • Multiple examples to demonstrate the applications in the field of finance
  • Sections with formal definitions of the various applied methods for readers to utilize throughout the book

Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance. The book is also an excellent reference for practitioners who apply statistical methods in quantitative finance.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

A modern approach to statistical learning and its applications through visualization methods

With a unique and innovative presentation, Multivariate Nonparametric Regression and Visualization provides readers with the core statistical concepts to obtain complete and accurate predictions when given a set of data. Focusing on nonparametric methods to adapt to the multiple types of data generating mechanisms, the book begins with an overview of classification and regression.

The book then introduces and examines various tested and proven visualization techniques for learning samples and functions. Multivariate Nonparametric Regression and Visualization identifies risk management, portfolio selection, and option pricing as the main areas in which statistical methods may be implemented in quantitative finance. The book provides coverage of key statistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, and nearest neighbor methods. Exploring the additional applications of nonparametric and semiparametric methods, Multivariate Nonparametric Regression and Visualization features:

Multivariate Nonparametric Regression and Visualization is an ideal textbook for upper-undergraduate and graduate-level courses on nonparametric function estimation, advanced topics in statistics, and quantitative finance. The book is also an excellent reference for practitioners who apply statistical methods in quantitative finance.

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