ANALYSIS OF ALGORITHMS FOR STABLE ESTIMATION OF COEFFICIENTS OF MULTIPLE LINEAR REGRESSION MODELS

A. A. Azaryan

Abstract


Computational experiments on model data were performed in order to study the effectiveness of the algorithms for realization of the least absolute deviations (LAD) method and the generalized method of the least absolute deviations (GLAD) when estimating the parameters of multiple linear regression models based on descent through the nodal straight lines. In addition, a comparative analysis of the algorithms of descent through nodal straight lines for LAD and GLAD with known exact and approximate methods to solve tasks (2) and (3) was carried out.


Keywords


linear regression model; the least absolute deviations method; generalized; computational complexity; comparative analysis.

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