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

Gonzalo Garcia-Donato; James O. Berger; Miguel A. Martinez-Beneito; Victor Pe\~na

arxiv: 1607.02993 · v1 · pith:7UJSLK5Vnew · submitted 2016-07-11 · 📊 stat.ME

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

James O. Berger , Gonzalo Garcia-Donato , Miguel A. Martinez-Beneito , Victor Pe\~na This is my paper

classification 📊 stat.ME

keywords selectionvariableassumptionsbayesianconsiderdimensionalexceedhigh

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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).

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

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