Search Results for author:
Found 7 papers, 2 papers with code
Integrated path stability selection
This yields a tighter bound on E(FP), resulting in a feature selection criterion that has higher sensitivity in practice and is better calibrated in terms of matching the target E(FP).
Reproducible Parameter Inference Using Bagged Posteriors
Under model misspecification, it is known that Bayesian posteriors often do not properly quantify uncertainty about true or pseudo-true parameters.
Fast and accurate approximation of the full conditional for gamma shape parameters
It turns out that the full conditional distribution of the gamma shape parameter is well approximated by a gamma distribution, even for small sample sizes, when the prior on the shape parameter is also a gamma distribution.
An elementary derivation of the Chinese restaurant process from Sethuraman's stick-breaking process
The Chinese restaurant process (CRP) and the stick-breaking process are the two most commonly used representations of the Dirichlet process.
Mixture models with a prior on the number of components
A natural Bayesian approach for mixture models with an unknown number of components is to take the usual finite mixture model with Dirichlet weights, and put a prior on the number of components---that is, to use a mixture of finite mixtures (MFM).
Methodology
A simple example of Dirichlet process mixture inconsistency for the number of components
For data assumed to come from a finite mixture with an unknown number of components, it has become common to use Dirichlet process mixtures (DPMs) not only for density estimation, but also for inferences about the number of components.
Inconsistency of Pitman-Yor process mixtures for the number of components
We show that this posterior is not consistent --- that is, on data from a finite mixture, it does not concentrate at the true number of components.
