Introducing localgauss, an R Package for Estimating and Visualizing Local Gaussian Correlation

Geir Drage Berentsen, Tore Selland Kleppe, Dag Bjarne Tjøstheim

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Quantifying non-linear dependence structures between two random variables is a challenging task. There exist several bona-fide dependence measures able to capture the strength of the non-linear association, but they typically give little information about how the variables are associated. This problem has been recognized by several authors and has given rise to the concept of local measures of dependence. A local measure of dependence is able to capture the “local” dependence structure in a particular region. The idea is that the global dependence structure is better described by a portfolio of local measures of dependence computed in different regions than a one-number measure of dependence. This paper introduces the R package localgauss which estimates and visualizes a measure of local dependence called local Gaussian correlation. The package provides a function for estimation, a function for local independence testing and corresponding functions for visualization purposes, which are all demonstrated with examples.

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