Additive spatial statistical models with weakly stationary process
assum...
We introduce Bayesian hierarchical models for predicting high-dimensiona...
Markov chain Monte Carlo (MCMC) is an all-purpose tool that allows one t...
Consider the setting where there are B>1 candidate statistical models, a...
Consider the situation where an analyst has a Bayesian statistical model...
It is increasingly understood that the assumption of stationarity is
unr...
The goal of this paper is to provide a way for statisticians to answer t...
Tracking and estimating Daily Fine Particulate Matter (PM2.5) is very
im...
Spatio-temporal change of support (STCOS) methods are designed for
stati...
We introduce a Bayesian approach for analyzing high-dimensional multinom...
Statistical agencies often publish multiple data products from the same
...