## 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
β¦ LIBER β¦
Stochastic matching pursuit for Bayesian variable selection
β Scribed by Ray-Bing Chen; Chi-Hsiang Chu; Te-You Lai; Ying Nian Wu
- Publisher
- Springer US
- Year
- 2009
- Tongue
- English
- Weight
- 411 KB
- Volume
- 21
- Category
- Article
- ISSN
- 0960-3174
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