269 citations · 335 across the 12 of their papers we have counts for
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stat.ME2017★ 6 cited
Bayesian Sparse Global-Local Shrinkage Regression for Selection of Grouped Variables
Zemei Xu, Daniel F. Schmidt, Enes Makalic +2
Most estimates for penalised linear regression can be viewed as posterior modes for an appropriate choice of prior distribution. Bayesian shrinkage methods, particularly the horses…
stat.ME2017
Minimum message length inference of the Poisson and geometric models using heavy-tailed prior distributions
Chi Kuen Wong, Enes Makalic, Daniel F. Schmidt
Minimum message length is a general Bayesian principle for model selection and parameter estimation that is based on information theory. This paper applies the minimum message leng…