Bayesian variable selection in high dimensional problems without assumptions on prior model probabilities

Abstract

We consider the problem of variable selection in linear models when $p$, the number of potential regressors, may exceed (and perhaps substantially) the sample size $n$ (which is possibly small).

References in corpus (1)

• Fully Bayes factors with a generalized g-prior

Cited by in corpus (1)

• Handling Factors in Variable Selection Problems