Title: A mathematical programming-based approach in piecewise regression optimisation by simultaneous considering variables

Authors: Mahsa Laari; Reza Kamranrad; Farnoosh Bagheri

Addresses: Department of Industrial Engineering, University of Science and Culture, Tehran, Iran ' Department of Industrial Engineering, University of Science and Culture, Tehran, Iran ' Department of Industrial Engineering, University of Science and Culture, Tehran, Iran

Abstract: Piecewise regression is one of the linear regression types which control variables could break. In this paper, we propose a new mathematical programming-based approach to optimise the piecewise regression model by simultaneous considering variables. To this aim, the break point and the regression model parameters so determined that the absolute error of prediction is minimised. Note that existing methods are designed only based on independent variables and simultaneous effects of variable are not considered in piecewise regression. Accordingly, in this paper, a new approach is developed to optimise the piecewise regression model by simultaneous considering variables. Results show that proposed method has better performance than the existing methods for fitting data with correlated control variables.

Keywords: piecewise regression model; mathematical programming; break points; optimisation.

DOI: 10.1504/IJQET.2018.097343

International Journal of Quality Engineering and Technology, 2018 Vol.7 No.2, pp.152 - 163

Received: 02 Nov 2017
Accepted: 06 Jul 2018
Published online: 15 Jan 2019 *

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