10.26731/2658-3704.2022.1(13).5-15
The article is devoted to the study of interpretive characteristics of non-elementary linear regression models. An algorithm for the approximate estimation of such models using the ordinary least squares and one of the possible strategies for their construction are considered. Using the statistical data built-in Gretl econometric package, a non-elementary linear regression with seven explanatory variables was construct. For this, for the first time, the variation of the binary operations minimum and maximum was used. The resulting model is characterized by a low degree of multicollinearity and significantly outperformed linear regression in terms of the coefficient of determination. The interpretation of the resulting model made it possible to identify new patterns in the functioning of the dependent variable, which are not available when using classical linear regression.
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