Abstract
The article is devoted to the construction of posinomial regression models with several monomes for each input variable. Such models generalize well-known polynomial regressions. Investigated by a posin with one variable and two monomes. The algorithm «A» of approximate estimation of posinomial regressions using the least squares method is proposed. The main disadvantage of the algorithm «A» is that due to the inter-monomic multicollinearity, the estimated posinomial regression may not be consistent with the meaningful meaning of the factors included in it. Therefore, algorithm «B» was developed, which guarantees not only the preservation of the meaningful meaning of the factors, but also the significance of all posinomial regression coefficients according to the Student's t-criterion. Algorithm «B» was implemented in the form of the POSITON-1 software package. The work of the software package is demonstrated by the example of solving a specific applied problem.
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