1.

Record Nr.

UNINA9910135024803321

Autore

Shevlyakov Georgy L.

Titolo

Robust correlation : theory and applications / / Georgy L. Shevlyakov, Hannu Oja

Pubbl/distr/stampa

Chichester, England : , : Wiley, , 2016

©2016

ISBN

1-119-26449-9

1-119-26453-7

1-119-26450-2

Descrizione fisica

1 online resource (353 p.)

Collana

Wiley Series in Probability and Statistics

THEi Wiley ebooks

Disciplina

519.5/37

Soggetti

Correlation (Statistics)

Mathematical statistics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Nota di contenuto

Cover; Title Page; Copyright; Dedication; Contents; Preface; Acknowledgements; About the Companion Website; Chapter 1 Introduction; 1.1 Historical Remarks; 1.2 Ontological Remarks; 1.2.1 Forms of data representation; 1.2.2 Types of data statistics; 1.2.3 Principal aims of statistical data analysis; 1.2.4 Prior information about data distributions and related approaches to statistical data analysis; References; Chapter 2 Classical Measures of Correlation; 2.1 Preliminaries; 2.2 Pearson's Correlation Coefficient: Definitions and Interpretations; 2.2.1 Introductory remarks

2.2.2 Correlation via regression2.2.3 Correlation via the coefficient of determination; 2.2.4 Correlation via the variances of the principal components; 2.2.5 Correlation via the cosine of the angle between the variable vectors; 2.2.6 Correlation via the ratio of two means; 2.2.7 Pearson's correlation coefficient between random events; 2.3 Nonparametric Measures of Correlation; 2.3.1 Introductory remarks; 2.3.2 The quadrant correlation coefficient; 2.3.3 The Spearman rank correlation coefficient; 2.3.4 The Kendall   -rank correlation coefficient;



2.3.5 Concluding remark

2.4 Informational Measures of Correlation2.5 Summary; References; Chapter 3 Robust Estimation of Location; 3.1 Preliminaries; 3.2 Huber's Minimax Approach; 3.2.1 Introductory remarks; 3.2.2 Minimax variance M-estimates of location; 3.2.3 Minimax bias M-estimates of location; 3.2.4 L-estimates of location; 3.2.5 R-estimates of location; 3.2.6 The relations between M-, L- and R-estimates of location; 3.2.7 Concluding remarks; 3.3 Hampel's Approach Based on Influence Functions; 3.3.1 Introductory remarks; 3.3.2 Sensitivity curve; 3.3.3 Influence function and its properties

3.3.4 Local measures of robustness3.3.5 B- and V-robustness; 3.3.6 Global measure of robustness: the breakdown point; 3.3.7 Redescending M-estimates; 3.3.8 Concluding remark; 3.4 Robust Estimation of Location: A Sequel; 3.4.1 Introductory remarks; 3.4.2 Huber's minimax variance approach in distribution density models of a non-neighborhood nature; 3.4.3 Robust estimation of location in distribution models with a bounded variance; 3.4.4 On the robustness of robust solutions: stability of least informative distributions; 3.4.5 Concluding remark; 3.5 Stable Estimation; 3.5.1 Introductory remarks

3.5.2 Variance sensitivity3.5.3 Estimation stability; 3.5.4 Robustness of stable estimates; 3.5.5 Maximin stable redescending M-estimates; 3.5.6 Concluding remarks; 3.6 Robustness Versus Gaussianity; 3.6.1 Introductory remarks; 3.6.2 Derivations of the Gaussian distribution; 3.6.3 Properties of the Gaussian distribution; 3.6.4 Huber's minimax approach and Gaussianity; 3.6.5 Concluding remarks; 3.7 Summary; References; Chapter 4 Robust Estimation of Scale; 4.1 Preliminaries; 4.1.1 Introductory remarks; 4.1.2 Estimation of scale in data analysis; 4.1.3 Measures of scale defined by functionals

4.2 M- and L-Estimates of Scale