Towards a Localized Version of Pearson's Correlation Coefficient
Владик Крейнович, Hung T. Nguyen, Berlin Wu
Abstract
Владик Крейнович, Hung T. Nguyen, Berlin Wu
Abstract
Pearson’s correlation coefficient is used to describe dependence between random variables X and Y . In some practical situations, however, we have strong correlation for some values X and/or Y and no correlation for other values ofX and Y . To describe such a local dependence, we come up with a natural localized version of Pearson’s correlation coefficient. We also study the properties of the newly defined localized coefficient. 1 Formulation of the Problem Pearson’s correlation coefficient: reminder. To describe relation between two random variables X and Y , Pearson’s correlation coefficient r is often used. This coefficient is defined as r[X,Y ] def = C[X,Y ] σ[X] · σ(Y ) , (1)
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Pearson’s correlation coefficient is used to describe dependence between random variables X and Y . In some practical situations, however, we have strong correlation for some values X and/or Y and no correlation for other values ofX and Y . To describe such a local dependence, we come up with a natural localized version of Pearson’s correlation coefficient. We also study the properties of the newly defined localized coefficient. 1 Formulation of the Problem Pearson’s correlation coefficient: reminder. To describe relation between two random variables X and Y , Pearson’s correlation coefficient r is often used. This coefficient is defined as r[X,Y ] def = C[X,Y ] σ[X] · σ(Y ) , (1)
Key concepts: Pearson product-moment correlation coefficient, Correlation coefficient, Fisher transformation, Distance correlation, Mathematics, Statistics, Correlation, Correlation ratio