Journal
BAYESIAN ANALYSIS
Volume 5, Issue 3, Pages 583-618Publisher
INT SOC BAYESIAN ANALYSIS
DOI: 10.1214/10-BA523
Keywords
Evolutionary Monte Carlo; Fast Scan Metropolis-Hastings scheme; linear Gaussian regression models; variable selection
Funding
- MRC [G060020609]
- Medical Research Council [G0801056B] Funding Source: researchfish
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available