A Simple Sampler for the Horseshoe Estimator

Enes Makalic, Daniel F. Schmidt

IEEE Signal Processing Letters · 2015 · 259 citations · 17 references

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Abstract

In this note we derive a simple Bayesian sampler for linear regression with the horseshoe hierarchy. A new interpretation of the horseshoe model is presented, and extensions to logistic regression and alternative hierarchies, such as horseshoe+, are discussed. Due to the conjugacy of the proposed hierarchy, Chib's algorithm may be used to easily compute the marginal likelihood of the model.

References

17