Title: A Regression Model for Fuzzy Initial Data.
Authors: Domrachev, V. G.; Poleshuk, O. M.
Abstract: A fuzzy combined linear regression model for fuzzy initial data, which are tolerant (L-R)-numbers with constraints on the functions L and R, is designed. The model is called combined since it is a combination of two regression models—a fuzzy model and a classical model. Its coefficients are determined as unimodal (L-R)-numbers. The solution method consists in determining weighted intervals for the tolerant (L-R)-numbers and then applying of the least-squares method.
Subjects: REGRESSION analysis; MATHEMATICAL statistics; FUZZY mathematics; INTERVAL analysis; LEAST squares
Publication: Automation & Remote Control, 2003, Vol 64, Issue 11, p1715
ISSN: 0005-1179
Publication type: Academic Journal
DOI: 10.1023/A:1027322111898

A Regression Model for Fuzzy Initial Data.

Domrachev, V. G.; Poleshuk, O. M.