MAXIMUM CONSISTENCY METHOD IN REGRESSION ANALYSIS
The article discusses a new method for estimating unknown parameters of a linear regression equation, which differs from traditional methods in that it is based not on minimizing approximation errors in a given metric, but on maximizing consistency in the behavior of the calculated and actual values of the output variable. Formally, this consistency is expressed in maximizing the number of coincidences of the signs of the increments of these values on all pairs of observation numbers in the sample. The proposed method is based on the author's works, in which a criterion for assessing the adequacy of regression models is proposed - the criterion of consistency of behavior (CCB), - its various modifications and methods of application are given. A numerical example is considered.