Variable Selection Using Nonlocal Priors in High-Dimensional Generalized Linear Models With Application to fMRI Data Analysis

High-dimensional variable selection is an important research topic in modern statistics. While methods using nonlocal priors have been thoroughly studied for variable selection in linear regression, the crucial high-dimensional model selection properties for nonlocal priors in generalized linear mod...

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Detalles Bibliográficos
Autores principales: Cao, Xuan, Lee, Kyoungjae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517378/
https://www.ncbi.nlm.nih.gov/pubmed/33286578
http://dx.doi.org/10.3390/e22080807

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517378/
https://www.ncbi.nlm.nih.gov/pubmed/33286578
http://dx.doi.org/10.3390/e22080807

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