Title : ( Goodman–Kruskal measure of association for fuzzy–categorized variables )
Authors: Seed Mahmood Taheri , GR. Hesamian ,
Full TextAbstract
The Goodman–Kruskal measure, which is a well-known measure of dependence for con- tingency tables, is generalized to the case when the variables of interest are categorized by linguistic terms rather than crisp sets. In addition, to test the hypothesis of independence in such contingency tables, a novel method of decision making is developed based on a concept of fuzzy p-value. The applicability of the proposed approach is explained using a numerical example.
Keywords
, fuzzy frequency, fuzzy category, fuzzy Goodman–Kruskal statistic, fuzzy p- value, fuzzy significance level, NSD index
@article{paperid:1027616,
author = {Taheri, Seed Mahmood and GR. Hesamian},
title = {Goodman–Kruskal measure of association for fuzzy–categorized variables},
journal = {Kybernetika},
year = {2011},
volume = {47},
number = {1},
month = {March},
issn = {0023-5954},
pages = {110--122},
numpages = {12},
keywords = {fuzzy frequency; fuzzy category; fuzzy Goodman–Kruskal statistic; fuzzy p-
value; fuzzy significance level; NSD index},
}
%0 Journal Article
%T Goodman–Kruskal measure of association for fuzzy–categorized variables
%A Taheri, Seed Mahmood
%A GR. Hesamian
%J Kybernetika
%@ 0023-5954
%D 2011
