Combined application of methods of maximum consistency and anti-robust parameter estimation in the construction of regression models

Abstract

Objective. The purpose of the study is to solve the problem of calculating the parameters of a linear regression model based on the joint application of anti-robust estimation methods and maximum consistency between the real and calculated values of the dependent variable in continuous form. Method. The unknown parameters of the model are calculated by reducing the original problem to a linear programming problem. Its solution should not cause computational difficulties due to the significant number of developed effective software tools. Result. The generated linear programming problem has a dimension acceptable for real situations. Conclusion. The results of solving a numerical example indicate the effectiveness of the method proposed in the work for calculating the parameters of a linear regression model based on the joint application of anti-robust estimation methods and maximum consistency. The final choice of parameter values remains with the model developer.

Keywords

• linear regression
• parameter identification
• least modulus methods
• antirobust estimation
• maximum consistency
• linear programming problem
• alternativeness