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A Markov Chain Genetic Algorithm Approach for Non-Parametric Posterior Distribution Sampling of Regression Parameters

This paper proposes a genetic algorithm-based Markov Chain approach that can be used for non-parametric estimation of regression coefficients and their statistical confidence bounds. The proposed approach can generate samples from an unknown probability density function if a formal functional form o...

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Gardado en:
Autor Principal: Parag C. Pendharkar
Formato: Artigo
Idioma:Inglês
Publicado: MDPI AG 2024-03-01
Series:Algorithms
Assuntos:
genetic algorithms
Markov Chains
regression
non-parametric estimation algorithm
Acceso en liña:https://www.mdpi.com/1999-4893/17/3/111
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