Models, systems, networks in economics, engineering, nature and society
Background. The construction of regression models of various complex objects in accordance with the objectives of the study is sometimes accompanied by the need to split the original data sample into subsamples (groups of observations) or the use of the so-called panel data. The purpose of the st...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penza State University Publishing House
2024-11-01
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| Series: | Модели, системы, сети в экономике, технике, природе и обществе |
| Subjects: | |
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| Summary: | Background. The construction of regression models of various complex objects
in accordance with the objectives of the study is sometimes accompanied by the need to split
the original data sample into subsamples (groups of observations) or the use of the so-called
panel data. The purpose of the study is to modify the method for calculating estimates of the
parameters of a linear regression equation developed earlier by one of the authors, using the
mixed estimation method. Materials and methods. To achieve this goal, the mathematical
apparatus for solving linear and linear Boolean programming problems was used. Results.
This goal is formalized by setting the task of automating the formation of the composition of
the index set of observation numbers to implement the antirobust estimation method within
the framework of the mixed estimation method by solving a linear Boolean programming
problem. Conclusions. The approach described in the work allows us to combine the advantages of the least modulus and anti-robust estimation methods when modeling. A regression model of freight turnover of road transport in the Russian Federation has been constructed that is adequate to the analyzed object. |
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| ISSN: | 2227-8486 |