A new approach using the genetic algorithm for parameter estimation in multiple linear regression with long-tailed symmetric distributed error terms: An application to the Covid-19 data

Maximum likelihood (ML) estimators of the model parameters in multiple linear regression are obtained using genetic algorithm (GA) when the distribution of the error terms is long-tailed symmetric. We compare the efficiencies of the ML estimators obtained using GA with the corresponding ML estimator...

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Detalles Bibliográficos
Autores principales: Yalçınkaya, Abdullah, Balay, İklim Gedik, Şenoǧlu, Birdal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413307/
https://www.ncbi.nlm.nih.gov/pubmed/34493885
http://dx.doi.org/10.1016/j.chemolab.2021.104372

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413307/
https://www.ncbi.nlm.nih.gov/pubmed/34493885
http://dx.doi.org/10.1016/j.chemolab.2021.104372

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