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Measuring directional dependency

Yadolah Dodge and Iraj Yadegari

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Abstract

In this article we propose new methods for finding the direction of dependency between two random variables which are related by a linear function.

Chapter information

Source
J. Antoch, M. Hušková and P.K. Sen, eds., Nonparametrics and Robustness in Modern Statistical Inference and Time Series Analysis: A Festschrift in honor of Professor Jana Jurečková (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2010), 62-69

Dates
First available in Project Euclid: 29 November 2010

Permanent link to this document
https://projecteuclid.org/euclid.imsc/1291044742

Digital Object Identifier
doi:10.1214/10-IMSCOLL706

Mathematical Reviews number (MathSciNet)
MR2808366

Subjects
Primary: 62J05: Linear regression
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

Keywords
asymptotic interpretation of the correlation coefficient causality correlation coefficient Kurtosis coefficient linear regression response variable coefficient of variation skewness coefficient

Rights
Copyright © 2010, Institute of Mathematical Statistics

Citation

Dodge, Yadolah; Yadegari, Iraj. Measuring directional dependency. Nonparametrics and Robustness in Modern Statistical Inference and Time Series Analysis: A Festschrift in honor of Professor Jana Jurečková, 62--69, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2010. doi:10.1214/10-IMSCOLL706. https://projecteuclid.org/euclid.imsc/1291044742


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References

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