22 citations · 58 across the 11 of their papers we have counts for
13 papers
Post-model-selection prediction for GLM's
Dean Dustin, Bertrand Clarke
We give two prediction intervals (PI) for Generalized Linear Models that take model selection uncertainty into account. The first is a straightforward extension of asymptotic norma…
A Cheat Sheet for Bayesian Prediction
Bertrand Clarke, Yuling Yao
This paper reviews the growing field of Bayesian prediction. Bayes point and interval prediction are defined and exemplified and situated in statistical prediction more generally.…
Testing for the Important Components of Posterior Predictive Variance
Dean Dustin, Bertrand Clarke
We give a decomposition of the posterior predictive variance using the law of total variance and conditioning on a finite dimensional discrete random variable. This random variable…
Predictive Criteria for Prior Selection Using Shrinkage in Linear Models
Dean Dustin, Bertrand Clarke, Jennifer Clarke
Choosing a shrinkage method can be done by selecting a penalty from a list of pre-specified penalties or by constructing a penalty based on the data. If a list of penalties for a c…
Model Selection via the VC-Dimension
Merlin Mpoudeu, Bertrand Clarke
We derive an objective function that can be optimized to give an estimator of the Vapnik- Chervonenkis dimension for model selection in regression problems. We verify our estimator…
Modeling association in microbial communities with clique loglinear models
Adrian Dobra, Camilo Valdes, Dragana Ajdic +2
There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequen…