Search Results for author: Enes Makalic

Found 2 papers, 1 papers with code

Sparse Horseshoe Estimation via Expectation-Maximisation

1 code implementation7 Nov 2022 Shu Yu Tew, Daniel F. Schmidt, Enes Makalic

A particular strength of our approach is that the M-step depends only on the form of the prior and it is independent of the form of the likelihood.

Log-Scale Shrinkage Priors and Adaptive Bayesian Global-Local Shrinkage Estimation

no code implementations8 Jan 2018 Daniel F. Schmidt, Enes Makalic

Simulations show that the adaptive log-$t$ procedure appears to always perform well, irrespective of the level of sparsity or signal-to-noise ratio of the underlying model.

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