Title :
Multivariate Linear Regression Model Based on Fuzzy Variable in Econometrics
Author :
Zou Kaiqi ; Zhou Xiaoyue ; Liu Ying
Author_Institution :
Sch. of Eng. & Inf., Dalian Univ., Dalian, China
Abstract :
Econometrics is based on economic data while the data represented by fuzzy sets can not be dealt with classical time series methods. In this paper the author proposes a new kind of variable named fuzzy variable of econometric model based on fuzzy membership function. The gap between fuzzy mathematics and econometrics is connected by the concept of fuzzy variable. An example of multivariate linear regression based on fuzzy variable is given to show how fuzzy variable can be used in econometrics.
Keywords :
econometrics; fuzzy set theory; regression analysis; econometrics; economic data; fuzzy membership function; fuzzy sets; fuzzy variable; multivariate linear regression model; time series methods; Artificial intelligence; Computational intelligence; Econometrics; Economic forecasting; Electronic mail; Fuzzy sets; Insurance; Linear regression; Mathematics; Technology management; econometrics; fuzzy variable; multivariate linear regression model;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.465
