## 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 Bayesianβinspired penalized maximum likelihood approach appropriate for highβdi
Bayesian Methods for Regression Using Surrogate Variables
β Scribed by David Manner; John W. Seaman Jr.; Dean M. Young
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 181 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0323-3847
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