Computing Parameter Estimates of a Homogeneous Nested Piecewise Linear Regression

Objective . The aim of the study is to develop an algorithm for identifying the parameters of a homogeneous nested piecewise linear regression model of the first type by the method of least modules. Method . Estimation of its unknown parameters is carried out with the help of reduction to the proble...

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Vydané v:Vestnik Dagestanskogo gosudarstvennogo tehničeskogo universiteta. Tehničeskie nauki (Online) Ročník 50; číslo 4; s. 115 - 120
Hlavní autori: Noskov, S. I., Belinskaya, S. I.
Médium: Journal Article
Jazyk:English
Russian
Vydavateľské údaje: Dagestan State Technical University 23.01.2024
Predmet:
dimension
homogeneous nested piecewise linear regression
least moduli method
linear boolean programming problem
parameter identification
ISSN:2073-6185, 2542-095X
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Abstract Objective . The aim of the study is to develop an algorithm for identifying the parameters of a homogeneous nested piecewise linear regression model of the first type by the method of least modules. Method . Estimation of its unknown parameters is carried out with the help of reduction to the problem of linear Boolean programming. Its solution should not cause computational difficulties due to a significant number of effective software tools - for example, the well-established and freely available program LPsolve on the Internet. Result . The generated linear programming problem has an acceptable dimension for solving practical modeling problems. Conclusion . The results of solving a numerical example indicate the effectiveness of the method proposed in the work for calculating parameter estimates for a homogeneous nested piecewise linear regression model of the first type by the method of least modules.
AbstractList Objective . The aim of the study is to develop an algorithm for identifying the parameters of a homogeneous nested piecewise linear regression model of the first type by the method of least modules. Method . Estimation of its unknown parameters is carried out with the help of reduction to the problem of linear Boolean programming. Its solution should not cause computational difficulties due to a significant number of effective software tools - for example, the well-established and freely available program LPsolve on the Internet. Result . The generated linear programming problem has an acceptable dimension for solving practical modeling problems. Conclusion . The results of solving a numerical example indicate the effectiveness of the method proposed in the work for calculating parameter estimates for a homogeneous nested piecewise linear regression model of the first type by the method of least modules.
Objective. The aim of the study is to develop an algorithm for identifying the parameters of a homogeneous nested piecewise linear regression model of the first type by the method of least modules. Method. Estimation of its unknown parameters is carried out with the help of reduction to the problem of linear Boolean programming. Its solution should not cause computational difficulties due to a significant number of effective software tools - for example, the well-established and freely available program LPsolve on the Internet. Result. The generated linear programming problem has an acceptable dimension for solving practical modeling problems. Conclusion. The results of solving a numerical example indicate the effectiveness of the method proposed in the work for calculating parameter estimates for a homogeneous nested piecewise linear regression model of the first type by the method of least modules.
Author Belinskaya, S. I.
Noskov, S. I.
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Cites_doi 10.1007/s11269-017-1584-y
10.21822/2073-6185-2023-50-1-123-129
10.1007/s10489-016-0827-6
10.1007/BF02924523
10.1007/s00477-018-1576-3
10.1007/s10588-013-9157-y
10.1007/s40953-017-0089-0
10.1007/s11222-022-10152-9
10.1007/s10958-017-3250-6
10.17084/20764359-2023-67-57
10.1007/s10898-009-9426-y
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SubjectTerms dimension
homogeneous nested piecewise linear regression
least moduli method
linear boolean programming problem
parameter identification
Title Computing Parameter Estimates of a Homogeneous Nested Piecewise Linear Regression
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