A Bayesian Perspective on Unreplicated Factorial Experiments Using Potential Outcomes

Multivariate Spatial-temporal Model for Birth Defects and Ambient Air Pollution Risk Assessment

Bayesian Inference of Dynamical Model Formulation In this presentation, we address a holistic set of challenges in ocean Bayesian nonlinear estimation: i) predict the probability distribution functions (pdfs) of large nonlinear ocean systems using stochastic partial differential equations, ii) assimilate data using Bayes' law with these pdfs, iii) predict the future data that optimally reduce uncertainties, and (iv) rank the known and learn the new model formulations themselves. Overall, we allow the joint inference of the state, equations, geometry, boundary conditions and initial conditions... Read more about StatClimatol: Pierre Lermusiaux

Atomic Data Uncertainties

Forecasting with Many Models in Finance and Economics using Large Data Sets and Parallel Computing

Frequentist Accuracy of Bayesian Estimates

Propensity Score Weighting for Covariate Balance Read more about ApplStatWksp: Alan Zaslavsky

On the influence of the seed graph in the preferential attachment model

A Bayesian Nonparametric Approach to Monotone Missing Data in Longitudinal Studies with Informative Missingness

Accelerating Exact MCMC with Subsets of Data

New approaches to Bayesian variable selection in high-dimensional settings

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Consistency of the Adaptive Multiple Importance Sampling