ArticleBayesian analysis2023
Shrinkage with shrunken shoulders: Gibbs sampling shrinkage model posteriors with guaranteed convergence rates.
Article in Bayesian analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- torchtree: Flexible Phylogenetic Model Development and Inference Using PyTorch.Systematic biology · 2026Article
- Random-Effects Substitution Models for Phylogenetics via Scalable Gradient Approximations.Systematic biology · 2024Article
- Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models.PLoS computational biology · 2024Article
- On the surprising effectiveness of a simple matrix exponential derivative approximation, with application to global SARS-CoV-2.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Shrinkage-based Random Local Clocks with Scalable Inference.Molecular biology and evolution · 2023Article
- Scalable gradients enable Hamiltonian Monte Carlo sampling for phylodynamic inference under episodic birth-death-sampling models.bioRxiv : the preprint server for biology · 2023Article
- Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in "LargeJournal of the American Statistical Association · 2023Article
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2 authors.
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Abstract
Use of continuous shrinkage priors - with a "spike" near zero and heavy-tails towards infinity - is an increasingly popular approach to induce sparsity in parameter estimates. When the parameters are only weakly identified by the likelihood, however, the posterior may end up with tails as heavy as the prior, jeopardizing robustness of inference. A natural solution is to "shrink the shoulders" of a shrinkage prior by lightening up its tails beyond a reasonable parameter range, yielding a
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