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stat.ML2022
Sparse Horseshoe Estimation via Expectation-Maximisation
Shu Yu Tew, Daniel F. Schmidt, Enes Makalic
The horseshoe prior is known to possess many desirable properties for Bayesian estimation of sparse parameter vectors, yet its density function lacks an analytic form. As such, it…
stat.ME2022
Introduction to minimum message length inference
Enes Makalic, Daniel F. Schmidt
The aim of this manuscript is to introduce the Bayesian minimum message length principle of inductive inference to a general statistical audience that may not be familiar with info…