Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Geir Drage Berentsen, Tore Selland Kleppe, Dag Bjarne Tjøstheim
Title: Introducing localgauss, an R Package for Estimating and Visualizing Local Gaussian Correlation
Abstract: 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.

Page views:: 2619. Submitted: 2012-10-19. Published: 2014-02-18.
Paper: Introducing localgauss, an R Package for Estimating and Visualizing Local Gaussian Correlation     Download PDF (Downloads: 2855)
localgauss_0.33.tar.gz: R source package Download (Downloads: 350; 47KB)
v56i12.R: R example code from the paper Download (Downloads: 432; 1KB)

DOI: 10.18637/jss.v056.i12

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.