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

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.