33 citations · 35 across the 5 of their papers we have counts for
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stat.CO2016
Sampling hyperparameters in hierarchical models: improving on Gibbs for high-dimensional latent fields and large data sets
Richard A. Norton, J. Andres Christen, Colin Fox
We consider posterior sampling in the very common Bayesian hierarchical model in which observed data depends on high-dimensional latent variables that, in turn, depend on relativel…
stat.CO2016
Tuning of MCMC with Langevin, Hamiltonian, and other stochastic autoregressive proposals
Richard A. Norton, Colin Fox
Proposals for Metropolis-Hastings MCMC derived by discretizing Langevin diffusion or Hamiltonian dynamics are examples of stochastic autoregressive proposals that form a natural wi…