Pages that link to "Item:Q3147824"

The following pages link to Geometric <i>L</i>² and <sup /><i>L</i>¹ convergence are equivalent for reversible Markov chains<sup /> (Q3147824):

Displaying 37 items.

• Spectral gap for open Jackson networks (Q272510) (← links)
• The spectral gap for quasi-birth and death processes (Q353599) (← links)
• Some universal estimates for reversible Markov chains (Q388849) (← links)
• Limit theorems for stationary Markov processes with \(L^{2}\)-spectral gap (Q424699) (← links)
• Some aspects of modeling dependence in copula-based Markov chains (Q444977) (← links)
• Convergence rates for reversible Markov chains without the assumption of nonnegative definite matrices (Q625800) (← links)
• Asymptotic optimality of isoperimetric constants (Q742109) (← links)
• Conditions for rapid mixing of parallel and simulated tempering on multimodal distributions (Q1024896) (← links)
• Spectral gap for jump processes by decomposition method (Q1042548) (← links)
• Algebraic convergence of Markov chains (Q1413683) (← links)
• Trace-class Monte Carlo Markov chains for Bayesian multivariate linear regression with non-Gaussian errors (Q1750005) (← links)
• Renewal theory and computable convergence rates for geometrically erdgodic Markov chains (Q1774194) (← links)
• Markov chain decomposition for convergence rate analysis (Q1872401) (← links)
• Equivalence of exponential ergodicity and \(L^ 2\)-exponential convergence for Markov chains. (Q1877399) (← links)
• Geometric ergodicity and the spectral gap of non-reversible Markov chains (Q1930854) (← links)
• Convergence rates for MCMC algorithms for a robust Bayesian binary regression model (Q1950912) (← links)
• On the convergence complexity of Gibbs samplers for a family of simple Bayesian random effects models (Q2065471) (← links)
• Convergence rates of two-component MCMC samplers (Q2136999) (← links)
• Adaptive Huber regression on Markov-dependent data (Q2145801) (← links)
• Spectral analysis of the zigzag process (Q2155514) (← links)
• Geometric convergence bounds for Markov chains in Wasserstein distance based on generalized drift and contraction conditions (Q2155517) (← links)
• High-dimensional MCMC with a standard splitting scheme for the underdamped Langevin diffusion (Q2233568) (← 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)
• A theoretical comparison of the data augmentation, marginal augmentation and PX-DA algorithms (Q2426614) (← links)
• On reparametrization and the Gibbs sampler (Q2454004) (← links)
• Small-world MCMC and convergence to multi-modal distributions: from slow mixing to fast mixing (Q2467120) (← links)
• The geometry of Markov chain limit theorems (Q2860797) (← links)
• Dimension-Independent MCMC Sampling for Inverse Problems with Non-Gaussian Priors (Q2945165) (← links)
• On some basic features of strictly stationary, reversible Markov chains (Q5012851) (← links)
• Approximations of geometrically ergodic reversible markov chains (Q5013245) (← links)
• MCMC Algorithms for Posteriors on Matrix Spaces (Q5057083) (← links)
• Computation of Expectations by Markov Chain Monte Carlo Methods (Q5256571) (← links)
• On the geometric ergodicity of Metropolis-Hastings algorithms (Q5429699) (← links)
• Non-reversible guided Metropolis kernel (Q6116753) (← links)
• Explicit convergence bounds for Metropolis Markov chains: isoperimetry, spectral gaps and profiles (Q6616881) (← links)
• Analysis of two-component Gibbs samplers using the theory of two projections (Q6620069) (← links)