Correlation coefficient evaluation for the fuzzy interval data
Chih-Ching Yang
Journal of Business Research, 2016, vol. 69, issue 6, 2138-2144
Abstract:
The issue of evaluating an appropriate correlation with fuzzy data is an important topic in the econometrics and management science, especially when the data sets illustrate uncertainty, inconsistence, and incompleteness. This study extends the concept of Pearson's correlation coefficient to compute the correlation coefficient of the data sets that are fuzzy in nature. However, no common proposal for such extension exists. This study proposes several ways to evaluate the correlation coefficient when the fuzzy data are with interval types. Two empirical studies show that the methods that this study proposes for evaluating the coefficient of fuzzy correlations are useful and efficient from the perspective of econometrics and management.
Keywords: Fuzzy correlation coefficient; Pearson's correlation coefficient; Fuzzy data; Fuzzy correlation with mean and standard deviation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0148296315006463
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:69:y:2016:i:6:p:2138-2144
DOI: 10.1016/j.jbusres.2015.12.021
Access Statistics for this article
Journal of Business Research is currently edited by A. G. Woodside
More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).