Evaluation of measurement accuracy and significance for linear models

Identification of a linear dependency, when exact solution obtained by standard methods does not meet the objective requirements, determines development of specific approaches for their numerical realization. A method to obtain approximate values of linear models parameters on experimental data, which is based on the use of the linear programming methodology and the duality theory, is presented. This method makes it possible to obtain approximate solutions that fulfill all requirements to the model and its parameters and to evaluate accuracy and significance of measurements. It is important for improving the procedure of construction of functional dependencies on the stage of planning experiments if they do not satisfy the authenticity criteria. The results of testing the proposed method for problems connected with research of chemical and socioeconomic systems are given.