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„Altogether, the book provides a very nice overview of nonparametric and semiparametric regression methods with interesting applications to problems in quantitative finance.“ (Mathematical Reviews, 1 October 2015)
Multivariate Nonparametric Regression and Visualization
With R and Applications to Finance
von Jussi KlemeläA modern approach to statistical learning and itsapplications through visualization methods
With a unique and innovative presentation, MultivariateNonparametric Regression and Visualization provides readerswith the core statistical concepts to obtain complete and accuratepredictions when given a set of data. Focusing on nonparametricmethods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification andregression.
The book then introduces and examines various tested and provenvisualization techniques for learning samples and functions. Multivariate Nonparametric Regression and Visualizationidentifies risk management, portfolio selection, and option pricingas the main areas in which statistical methods may be implementedin quantitative finance. The book provides coverage of keystatistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, andnearest neighbor methods. Exploring the additional applications ofnonparametric and semiparametric methods, MultivariateNonparametric Regression and Visualization features:
* An extensive appendix with R-package training material toencourage duplication and modification of the presentedcomputations and research
* Multiple examples to demonstrate the applications in the fieldof finance
* Sections with formal definitions of the various applied methodsfor readers to utilize throughout the book
Multivariate Nonparametric Regression and Visualizationis an ideal textbook for upper-undergraduate and graduate-levelcourses on nonparametric function estimation, advanced topics instatistics, and quantitative finance. The book is also an excellentreference for practitioners who apply statistical methods inquantitative finance.
With a unique and innovative presentation, MultivariateNonparametric Regression and Visualization provides readerswith the core statistical concepts to obtain complete and accuratepredictions when given a set of data. Focusing on nonparametricmethods to adapt to the multiple types of data generatingmechanisms, the book begins with an overview of classification andregression.
The book then introduces and examines various tested and provenvisualization techniques for learning samples and functions. Multivariate Nonparametric Regression and Visualizationidentifies risk management, portfolio selection, and option pricingas the main areas in which statistical methods may be implementedin quantitative finance. The book provides coverage of keystatistical areas including linear methods, kernel methods, additive models and trees, boosting, support vector machines, andnearest neighbor methods. Exploring the additional applications ofnonparametric and semiparametric methods, MultivariateNonparametric Regression and Visualization features:
* An extensive appendix with R-package training material toencourage duplication and modification of the presentedcomputations and research
* Multiple examples to demonstrate the applications in the fieldof finance
* Sections with formal definitions of the various applied methodsfor readers to utilize throughout the book
Multivariate Nonparametric Regression and Visualizationis an ideal textbook for upper-undergraduate and graduate-levelcourses on nonparametric function estimation, advanced topics instatistics, and quantitative finance. The book is also an excellentreference for practitioners who apply statistical methods inquantitative finance.
