Robust correlation: theory and applications
This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data.--
Read More ↓Title Statements
- Full title :Robust correlation : theory and applications / Georgy L. Shevlyakov, Peter the Great Saint-Petersburg Polytechnic University, Russia, Hannu Oja, University Of Turku, Finland.
Summary
This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data.--
Read More ↓Edition Statements
- Publication Date:2016.
Publication Statements
- Publisher(s):Wiley
- Place of Publication:Chichester, West Sussex
- Language:eng
- Publication Date:2016.
The Physical Object
- Description:xvi, 319 pages ; : 24 cm.
Edition Identifiers
- ISBN:9781118493458, 1118493451
- oclc:ocn948426928
- LC Classification:QA278.2
- Dewey Decimal:519.5/37
Table of Contents
Machine generated contents note: 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 -- 2.1.Preliminaries -- 2.2.Pearson's Correlation Coefficient: Definitions and Interpretations -- 2.2.1.Introductory remarks -- 2.2.2.Correlation via regression -- 2.2.3.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
Note continued: 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 robus…
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