Bayesian Variable Selection in Structured High-Dimensional Covariate Spaces With Applications in Genomics

@inproceedings{Fan2009BayesianVS,
  title={Bayesian Variable Selection in Structured High-Dimensional Covariate Spaces With Applications in Genomics},
  author={Fan and Rong Li and Reyes Nancy and Zhang},
  year={2009}
}
We consider the problem of variable selection in regression modeling in high-dimensional spaces where there is known structure among the covariates. This is an unconventional variable selection problem for two reasons: (1) The dimension of the covariate space is comparable, and often much larger, than the number of subjects in the study, and (2) the covariate space is highly structured, and in some cases it is desirable to incorporate this structural information in to the model building process… CONTINUE READING
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