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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主要作者:	Parag C. Pendharkar
格式:	Artigo
語言:	Inglês
出版:	MDPI AG 2024-03-01
叢編:	Algorithms
主題:	genetic algorithms Markov Chains regression non-parametric estimation algorithm
在線閱讀:	https://www.mdpi.com/1999-4893/17/3/111
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