1
Master's degree in Statistics, Ferdowsi University of Mashhad
2
Professor of Statistics, Ferdowsi University of Mashhad
Abstract
In this article, the problem of collinearity in the regression model is first introduced, and the method of detecting collinearity and ways to eliminate collinearity are discussed. Next, preliminary definitions of information theory are given, and finally, using information theory, collinearity in the regression model is identified and a solution to eliminate it is proposed.
Shakiba, F. & Mohtashami Barzadran, G. (2016). Detecting and Eliminating Collinearity in Regression Models Using Information Theory. Andishe_ye Amari, 21(1), 13-21.
MLA
Shakiba, F., & Mohtashami Barzadran, G. "Detecting and Eliminating Collinearity in Regression Models Using Information Theory", Andishe_ye Amari, 21, 1, 2016, 13-21.
HARVARD
Shakiba F., Mohtashami Barzadran G. (2016). 'Detecting and Eliminating Collinearity in Regression Models Using Information Theory', Andishe_ye Amari, 21(1), pp. 13-21.
CHICAGO
F. Shakiba & G. Mohtashami Barzadran, "Detecting and Eliminating Collinearity in Regression Models Using Information Theory," Andishe_ye Amari, 21 1 (2016): 13-21,
VANCOUVER
Shakiba F., Mohtashami Barzadran G. Detecting and Eliminating Collinearity in Regression Models Using Information Theory. Andishe_ye Amari. 2016;21(1):13-21 (In Persian).
