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Conjugate priors and variable selection for Bayesian quantile regression

✍ Scribed by Alhamzawi, Rahim; Yu, Keming


Book ID
122275151
Publisher
Elsevier Science
Year
2013
Tongue
English
Weight
299 KB
Volume
64
Category
Article
ISSN
0167-9473

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## Abstract Variable selection in regression with very big numbers of variables is challenging both in terms of model specification and computation. We focus on genetic studies in the field of survival, and we present a Bayesian‐inspired penalized maximum likelihood approach appropriate for high‐di