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stat.CO2019
Bayesian inference for high-dimensional nonstationary Gaussian processes
Mark D. Risser, Daniel Turek
In spite of the diverse literature on nonstationary spatial modeling and approximate Gaussian process (GP) methods, there are no general approaches for conducting fully Bayesian in…
stat.CO2015
Automated Parameter Blocking for Efficient Markov-Chain Monte Carlo Sampling
Daniel Turek, Perry de Valpine, Christopher J. Paciorek +1
Markov chain Monte Carlo (MCMC) sampling is an important and commonly used tool for the analysis of hierarchical models. Nevertheless, practitioners generally have two options for…