Pages that link to "Item:Q2313288"

The following pages link to Convergence complexity analysis of Albert and Chib's algorithm for Bayesian probit regression (Q2313288):

Displaying 10 items.

• Convergence analysis of a collapsed Gibbs sampler for Bayesian vector autoregressions (Q2044318) (← links)
• On the convergence complexity of Gibbs samplers for a family of simple Bayesian random effects models (Q2065471) (← links)
• Wasserstein-based methods for convergence complexity analysis of MCMC with applications (Q2117437) (← links)
• On the limitations of single-step drift and minorization in Markov chain convergence analysis (Q2240862) (← links)
• Convergence complexity analysis of Albert and Chib's algorithm for Bayesian probit regression (Q2313288) (← links)
• Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models With Shrinkage Priors (Q5066449) (← links)
• Markov Kernels Local Aggregation for Noise Vanishing Distribution Sampling (Q5885821) (← links)
• Complexity results for MCMC derived from quantitative bounds (Q6104001) (← links)
• Exact convergence analysis for metropolis–hastings independence samplers in Wasserstein distances (Q6198959) (← links)
• Dimension-free mixing times of Gibbs samplers for Bayesian hierarchical models (Q6608672) (← links)