On weighted possibilistic informational coefficient of correlation

R. Fullér, István Á Harmati, P. Várlaki, I. Rudas

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In their previous works Fullér et al. introduced the notions of weighted possibilistic correlation coefficient and correlation ratio as measures of dependence between possibility distributions (fuzzy numbers). In this paper we introduce a new measure of strength of dependence between marginal possibility distributions, which is based on the informational coefficient of correlation. We will show some examples that demonstrate some good properties of the proposed measure.

Original languageEnglish
Pages (from-to)592-599
Number of pages8
JournalInternational Journal of Mathematical Models and Methods in Applied Sciences
Volume6
Issue number4
Publication statusPublished - 2012

Fingerprint

Possibility Distribution
Measures of Dependence
Coefficient
Marginal Distribution
Fuzzy numbers
Correlation coefficient
Demonstrate

Keywords

  • Correlation
  • Fuzzy number
  • Measure of dependence
  • Mutual information
  • Possibility distribution

ASJC Scopus subject areas

  • Applied Mathematics
  • Computational Mathematics
  • Mathematical Physics
  • Modelling and Simulation

Cite this

@article{015e6e5d4fb9499a82a20a7be9fd402f,
title = "On weighted possibilistic informational coefficient of correlation",
abstract = "In their previous works Full{\'e}r et al. introduced the notions of weighted possibilistic correlation coefficient and correlation ratio as measures of dependence between possibility distributions (fuzzy numbers). In this paper we introduce a new measure of strength of dependence between marginal possibility distributions, which is based on the informational coefficient of correlation. We will show some examples that demonstrate some good properties of the proposed measure.",
keywords = "Correlation, Fuzzy number, Measure of dependence, Mutual information, Possibility distribution",
author = "R. Full{\'e}r and Harmati, {Istv{\'a}n {\'A}} and P. V{\'a}rlaki and I. Rudas",
year = "2012",
language = "English",
volume = "6",
pages = "592--599",
journal = "International Journal of Mathematical Models and Methods in Applied Sciences",
issn = "1998-0140",
publisher = "North Atlantic University Union NAUN",
number = "4",

}

TY - JOUR

T1 - On weighted possibilistic informational coefficient of correlation

AU - Fullér, R.

AU - Harmati, István Á

AU - Várlaki, P.

AU - Rudas, I.

PY - 2012

Y1 - 2012

N2 - In their previous works Fullér et al. introduced the notions of weighted possibilistic correlation coefficient and correlation ratio as measures of dependence between possibility distributions (fuzzy numbers). In this paper we introduce a new measure of strength of dependence between marginal possibility distributions, which is based on the informational coefficient of correlation. We will show some examples that demonstrate some good properties of the proposed measure.

AB - In their previous works Fullér et al. introduced the notions of weighted possibilistic correlation coefficient and correlation ratio as measures of dependence between possibility distributions (fuzzy numbers). In this paper we introduce a new measure of strength of dependence between marginal possibility distributions, which is based on the informational coefficient of correlation. We will show some examples that demonstrate some good properties of the proposed measure.

KW - Correlation

KW - Fuzzy number

KW - Measure of dependence

KW - Mutual information

KW - Possibility distribution

UR - http://www.scopus.com/inward/record.url?scp=84871039897&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84871039897&partnerID=8YFLogxK

M3 - Article

VL - 6

SP - 592

EP - 599

JO - International Journal of Mathematical Models and Methods in Applied Sciences

JF - International Journal of Mathematical Models and Methods in Applied Sciences

SN - 1998-0140

IS - 4

ER -