Convergence rates of two-component MCMC samplers

Cites Work

Geometric ergodicity of the Bayesian Lasso
Markov chain Monte Carlo estimation of quantiles
Geometric ergodicity of random scan Gibbs samplers for hierarchical one-way random effects models
Positivity of hit-and-run and related algorithms
A gentle guide to the basics of two projections theory
Gibbs sampling, exponential families and orthogonal polynomials
Comment: ``Gibbs sampling, exponential families, and orthogonal polynomials
Comment: On random scan Gibbs samplers
Markov chain Monte Carlo: can we trust the third significant figure?
Spectral bounds for certain two-factor non-reversible MCMC algorithms
On the Markov chain central limit theorem
Error bounds for the method of alternating projections
Comparing sweep strategies for stochastic relaxation
On rates of convergence of stochastic relaxation for Gaussian and non- Gaussian distributions
Geometric ergodicity of Gibbs and block Gibbs samplers for a hierarchical random effects model
A note on Metropolis-Hastings kernels for general state spaces
Two convergence properties of hybrid samplers
Information bounds for Gibbs samplers
Geometric ergodicity and hybrid Markov chains
Honest exploration of intractable probability distributions via Markov chain Monte Carlo.
Convergence control methods for Markov chain Monte Carlo algorithms
Geometric ergodicity of Pólya-Gamma Gibbs sampler for Bayesian logistic regression with a flat prior
Strong consistency of multivariate spectral variance estimators in Markov chain Monte Carlo
Convergence analysis of the block Gibbs sampler for Bayesian probit linear mixed models with improper priors
Coordinate selection rules for Gibbs sampling
Sufficient burn-in for Gibbs samplers for a hierarchical random effects model.
Markov chains for exploring posterior distributions. (With discussion)
Rates of convergence of the Hastings and Metropolis algorithms
Convergence properties of the Gibbs sampler for perturbations of Gaussians
Convergence rates for MCMC algorithms for a robust Bayesian binary regression model
Multivariate initial sequence estimators in Markov chain Monte Carlo
Convergence analysis of a collapsed Gibbs sampler for Bayesian vector autoregressions
Batch means and spectral variance estimators in Markov chain Monte Carlo
Markov Chains and De-initializing Processes
Hybrid Samplers for Ill-Posed Inverse Problems
Geometric L² and ^{L¹ convergence are equivalent for reversible Markov chains}
Fixed-Width Output Analysis for Markov Chain Monte Carlo
Handbook of Markov Chain Monte Carlo
The Calculation of Posterior Distributions by Data Augmentation
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
10.—Norm Inequalities for C*-algebras
The Norm of the Sum of Two Projections
Covariance structure of the Gibbs sampler with applications to the comparisons of estimators and augmentation schemes
On the geometric ergodicity of hybrid samplers
On the applicability of regenerative simulation in Markov chain Monte Carlo
Multivariate output analysis for Markov chain Monte Carlo
Assessing and Visualizing Simultaneous Simulation Error
Convergence of Conditional Metropolis-Hastings Samplers
On random- and systematic-scan samplers
Geometric Ergodicity of van Dyk and Meng's Algorithm for the Multivariate Student'stModel
On the Geometric Ergodicity of Two-Variable Gibbs Samplers
Component-wise Markov chain Monte Carlo: uniform and geometric ergodicity under mixing and composition
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