On one algorithm of generating nonlinear regression models and its computer realization

MIREA Russian Technological University (M.V. Lomonosov Institute of Fine Chemical Technologies), 86, Vernadskogo pr., 119454 Moscow, Russia

^* Corresponding author: skvorivan@mail.ru

Abstract

The tasks of statistical processing of experimental data arise in different areas of human activity. In this regard, the development of algorithms and corresponding computer programs that allow such processing and satisfy certain conditions is an important task. The present work is carried out within the framework of the aforementioned field of research; an algorithm for generating a series of nonlinear regression models of a special type is proposed, and a brief description of the corresponding computer program is given. The proposed algorithm is iterative in nature: each subsequent model is built on the basis of the previous one according to some rule. This process begins with the construction of the simplest, linear model. For all the models obtained, a number of their statistical characteristics are calculated. The corresponding computer program is written in Java. The process of building models is managed by a some way by the user working with this program. In addition, in the paper a number of illustrative examples of constructing regression models using the developed program is given. The analysis of the obtained results is fulfilled, showing the advantages of the proposed methodology in comparison with the methodology of standard linear regression. The proposed procedure, in fact, allows us to pass from some initial linear regression model obtained at the first step of research to another model of better quality, without changing the initial set of empirical data. The presence of many final models makes it possible to select the best variants from them.