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Leguey Vitoriano
Ignacio

Larrañaga Múgica
Pedro María

Bielza Lozoya
María Concepción

Kato
Shogo
A circularlinear dependence measure under JohnsonWehrly distributions and its application in Bayesian networks
Elsevier
byncnd
unpub
 matematicas
 informatica
public
Circularlinear mutual information; Treestructured Bayesian network; Dependence measures; Directional statistics
Circular data jointly observed with linear data are common in various disciplines. Since circular data require different techniques than linear data, it is often misleading to use usual dependence measures for joint data of circular and linear observations. Moreover, although a mutual information measure between circular variables exists, the measure has drawbacks in that it is defined only for a bivariate extension of the wrapped Cauchy distribution and has to be approximated using numerical methods. In this paper, we introduce two measures of dependence, namely, (i) circularlinear mutual information as a measure of dependence between circular and linear variables and (ii) circularcircular mutual information as a measure of dependence between two circular variables. It is shown that the expression for the proposed circularlinear mutual information can be greatly simplified for a subfamily of Johnson–Wehrly distributions. We apply these two dependence measures to learn a circularlinear treestructured Bayesian network that combines circular and linear variables. To illustrate and evaluate our proposal, we perform experiments with simulated data. We also use a real meteorological data set from different European stations to create a circularlinear treestructured Bayesian network model.
published
201906
Information Sciences
486
240253
10.1016/j.ins.2019.01.080
ETSI_Informatica
Inteligencia_Artificial
TRUE
00200255
https://www.sciencedirect.com/science/article/pii/S0020025519300581?via%3Dihub

MINECO
C08002009
Cajal Blue Brain Project

CM
S2013/ICE2845
CASICAMCM
Conceptos y aplicaciones de los sistemas inteligentes

MINECO
FPU13/01941

MINECO
TIN2016796842P