3 papers
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.AP2018
Diversity of Artists in Major U.S. Museums
Chad M. Topaz, Bernhard Klingenberg, Daniel Turek +6
The U.S. art museum sector is grappling with diversity. While previous work has investigated the demographic diversity of museum staffs and visitors, the diversity of artists in th…
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…