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Handbook of Bayesian Variable Selection
by Mahlet G. Tadesse (Editor), Marina Vannucci (Editor)
The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection. The topics covered include spike-and-slab priors, continuous shrinkage priors, Bayes factors, Bayesian model averaging, partitioning methods, as well as variable selection in decision trees and edge selection in graphical models. The handbook targets graduate students and established researchers who seek to understand the latest developments in the field. It also provides a valuable reference for all interested in applying existing methods and/or pursuing methodological extensions.
- Publisher : Chapman and Hall/CRC; 1st edition (December 24, 2021)
- Publication date : December 24, 2021
- Language : English
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