56 citations · 64 across the 5 of their papers we have counts for
5 papers
A Modified Gibbs Sampler on General State Spaces
Alicia A. Johnson, James M. Flegal
We present a modified Gibbs sampler for general state spaces. We establish that this modification can lead to substantial gains in statistical efficiency while maintaining the over…
Geometric Ergodicity & Scanning Strategies For Two-Component Gibbs Samplers
Alicia A. Johnson, Owen Burbank
In any Markov chain Monte Carlo analysis, rapid convergence of the chain to its target probability distribution is of practical and theoretical importance. A chain that converges a…
Component-Wise Markov Chain Monte Carlo: Uniform and Geometric Ergodicity under Mixing and Composition
Alicia A. Johnson, Galin L. Jones, Ronald C. Neath
It is common practice in Markov chain Monte Carlo to update the simulation one variable (or sub-block of variables) at a time, rather than conduct a single full-dimensional update.…
Comment: Gibbs Sampling, Exponential Families, and Orthogonal Polynomials
Galin L. Jones, Alicia A. Johnson
Comment on ``Gibbs Sampling, Exponential Families, and Orthogonal Polynomials'' [arXiv:0808.3852]
Gibbs Sampling for a Bayesian Hierarchical General Linear Model
Alicia A. Johnson, Galin L. Jones
We consider a Bayesian hierarchical version of the normal theory general linear model which is practically relevant in the sense that it is general enough to have many applications…