Bayesian methods outperform classical ones on prediction error in correlated weak-signal settings, with Horseshoe providing near-nominal coverage and Lasso tying Spike-and-Slab on variable selection F1 score.
Stan: Aprobabilistic programming language.Journal of Statistical Software, 76(1):1–32
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Sparse Regression under Correlation and Weak Signals: A Reproducible Benchmark of Classical and Bayesian Methods
Bayesian methods outperform classical ones on prediction error in correlated weak-signal settings, with Horseshoe providing near-nominal coverage and Lasso tying Spike-and-Slab on variable selection F1 score.