期刊
BAYESIAN ANALYSIS
卷 5, 期 3, 页码 583-618出版社
INT SOC BAYESIAN ANALYSIS
DOI: 10.1214/10-BA523
关键词
Evolutionary Monte Carlo; Fast Scan Metropolis-Hastings scheme; linear Gaussian regression models; variable selection
资金
- MRC [G060020609]
- Medical Research Council [G0801056B] Funding Source: researchfish
Implementing Bayesian variable selection for linear Gaussian regression models for analysing high dimensional data sets is of current interest in many fields. In order to make such analysis operational, we propose a new sampling algorithm based upon Evolutionary Monte Carlo and designed to work under the large p, small n paradigm, thus making fully Bayesian multivariate analysis feasible, for example, in genetics/genomics experiments. Two real data examples in genomics are presented, demonstrating the performance of the algorithm in a space of up to 10, 000 covariates. Finally the methodology is compared with a recently proposed search algorithms in an extensive simulation study.
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