20 citations · 22 across the 8 of their papers we have counts for
9 papers
Uncertainty Quantification in Bayesian Clustering
Garritt L. Page, Andrés F. Barrientos, David B. Dahl +1
Bayesian clustering methods have the widely touted advantage of providing a probabilistic characterization of uncertainty in clustering through the posterior distribution. An amazi…
Quantile Slice Sampling
Matthew J. Heiner, Samuel B. Johnson, Joshua R. Christensen +1
We propose and demonstrate a novel, effective approach to slice sampling. Using the probability integral transform, we first generalize Neal's shrinkage algorithm, standardizing th…
Comparison and Bayesian Estimation of Feature Allocations
David B. Dahl, Devin J. Johnson, R. Jacob Andros
Feature allocation models postulate a sampling distribution whose parameters are derived from shared features. Bayesian models place a prior distribution on the feature allocation,…
Writing R Extensions in Rust
David B. Dahl
This paper complements "Writing R Extensions," the official guide for writing R extensions, for those interested in developing R packages using Rust. It highlights idiosyncrasies o…
The Attraction Indian Buffet Distribution
Richard L. Warr, David B. Dahl, Jeremy M. Meyer +1
We propose the attraction Indian buffet distribution (AIBD), a distribution for binary feature matrices influenced by pairwise similarity information. Binary feature matrices are u…
Cluster Analysis via Random Partition Distributions
David B. Dahl, Jacob Andros, J. Brandon Carter
Hierarchical and k-medoids clustering are deterministic clustering algorithms based on pairwise distances. Using these same pairwise distances, we propose a novel stochastic cluste…