Nonparametric Methods in Multivariate Analysis PDF Download

Author: Madan Lal Puri
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 464

View

Book Description

Author: Hannu Oja
Publisher: Springer Science & Business Media
ISBN: 1441904689
Category : Mathematics
Languages : en
Pages : 239

View

Book Description
This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory. Hannu Oja is an academy professor and a professor in biometry in the University of Tampere. He has authored and coauthored numerous research articles in multivariate nonparametrical and robust methods as well as in biostatistics.

Author: Jussi Sakari Klemelä
Publisher: John Wiley & Sons
ISBN: 1118593502
Category : Mathematics
Languages : en
Pages : 317

View

Book Description
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.

Author: P.K. Sen
Publisher:
ISBN:
Category :
Languages : en
Pages : 440

View

Book Description

Author: Hannu Oja
Publisher: Springer
ISBN: 9781441904690
Category : Mathematics
Languages : en
Pages : 234

View

Book Description

Author: Jean Dickinson Gibbons
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 504

View

Book Description

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 28

View

Book Description
Multivariate statistical procedures developed under normality assumptions are well advanced. Some of these procedures claim robustness properties, especially in a large sample situation, that may serve to broaden their range of application. Nonparametric methods for multivariate analysis have been pursued, but their more complete development awaits further research. This report considers nonparametric multivariate hypothesis testing in both one- and two-sample situations. Comparable univariate procedures do not extend readily to higher dimensions. The methods considered are based on the properties of statistically equivalent blocks. A new approach using a proximity-based cutting function for block construction is described. Statistically equivalent blocks, while holding the promise of important practical application, has received limited research attention.

Author: Jayant V Deshpande
Publisher: World Scientific
ISBN: 981466359X
Category : Mathematics
Languages : en
Pages : 279

View

Book Description
The number of books on Nonparametric Methodology is quite small as compared to, say, on Design of Experiments, Regression Analysis, Multivariate Analysis, etc. Because of being perceived as less effective, nonparametric methods are still the second choice. Actually, it has been demonstrated time and again that they are useful. We feel that there is still need for proper texts/applications/reference books on Nonparametric Methodology.This book will introduce various types of data encountered in practice and suggest the appropriate nonparametric methods, discuss their properties through null and non-null distributions whenever possible and demonstrate the very minor loss in power and efficiency in the nonparametric method, if any.The book will cover almost all topics of current interest such as bootstrapping, ranked set sampling, techniques for censored data and Bayesian analysis under nonparametric set ups.

Author: Klaus Nordhausen
Publisher: Springer
ISBN: 3319224042
Category : Mathematics
Languages : en
Pages : 513

View

Book Description
Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

Author: Thomas P. Hettmansperger
Publisher: John Wiley & Sons
ISBN:
Category : Nonparametric statistics
Languages : en
Pages : 492

View

Book Description
Offering an alternative to traditional statistical procedures which are based on least squares fitting, the authors cover such topics as one and two sample location models, linear models, and multivariate models. Both theory and applications are examined.