Título: GIBBS SAMPLING APPROACH TO VARIABLE SELECTION IN LINEAR REGRESSION WITH OUTLIER VALUES
Autores: Atilla YARDIMCI
Aydın ERAR
Fecha: 2010-08-18
Publicador: Gazi University Journal of Science
Fuente:
Tipo: Peer-reviewed Article
Tema: Key Words: Bayesian variable selection, prior distribution, Gibbs sampling, Markov Chain Monte Carlo, outlier values, entropy
Descripción: ABSTRACTIn this study, Gibbs sampling has been applied to the variable selection in the linear regression model with outlier values. Gibbs sampling has been compared with classical variable selection criteria by using dummy data with different β and priors.
Idioma: Inglés

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