Pages that link to "Item:Q1922398"
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The following pages link to Rates of convergence of the Hastings and Metropolis algorithms (Q1922398):
Displaying 50 items.
- Polynomial convergence rates of Markov chains (Q1872407) (← links)
- Practical drift conditions for subgeometric rates of convergence. (Q1879912) (← links)
- Rates of convergence of the Hastings and Metropolis algorithms (Q1922398) (← links)
- Convergence properties of the Gibbs sampler for perturbations of Gaussians (Q1922399) (← links)
- Central limit theorem for triangular arrays of non-homogeneous Markov chains (Q1934366) (← links)
- Adaptive Gibbs samplers and related MCMC methods (Q1948684) (← links)
- A Metropolis-Hastings based method for sampling from the \(G\)-Wishart distribution in Gaussian graphical models (Q1952170) (← links)
- Langevin-type models II: Self-targeting candidates for MCMC algorithms (Q1961834) (← links)
- Perturbation bounds for Monte Carlo within metropolis via restricted approximations (Q1986021) (← links)
- Mixture of transmuted Pareto distribution: properties, applications and estimation under Bayesian framework (Q1989303) (← links)
- Fast mixing of Metropolis-Hastings with unimodal targets (Q1990039) (← links)
- Convergence of contrastive divergence algorithm in exponential family (Q1991693) (← links)
- Irreducibility and geometric ergodicity of Hamiltonian Monte Carlo (Q1996782) (← links)
- Fourier transform MCMC, heavy-tailed distributions, and geometric ergodicity (Q1998313) (← links)
- f-SAEM: a fast stochastic approximation of the EM algorithm for nonlinear mixed effects models (Q2008004) (← links)
- A Metropolis-class sampler for targets with non-convex support (Q2058894) (← links)
- Large deviations for the empirical measure of the zig-zag process (Q2075330) (← links)
- Deep composition of tensor-trains using squared inverse Rosenblatt transports (Q2098237) (← links)
- Exact and computationally efficient Bayesian inference for generalized Markov modulated Poisson processes (Q2114041) (← links)
- Variance reduction for additive functionals of Markov chains via martingale representations (Q2114045) (← links)
- Convergence rates of two-component MCMC samplers (Q2136999) (← links)
- Oracle lower bounds for stochastic gradient sampling algorithms (Q2137007) (← links)
- Stochastic zeroth-order discretizations of Langevin diffusions for Bayesian inference (Q2137043) (← links)
- On the theoretical properties of the exchange algorithm (Q2137050) (← links)
- Exact convergence analysis of the independent Metropolis-Hastings algorithms (Q2137055) (← links)
- Saddlepoint approximation for the generalized inverse Gaussian Lévy process (Q2141580) (← links)
- Variance bounding of delayed-acceptance kernels (Q2157432) (← links)
- Directed hybrid random networks mixing preferential attachment with uniform attachment mechanisms (Q2164797) (← links)
- On a Metropolis-Hastings importance sampling estimator (Q2180048) (← links)
- Optimal scaling of random-walk Metropolis algorithms on general target distributions (Q2196541) (← links)
- Geometric ergodicity of a Metropolis-Hastings algorithm for Bayesian inference of phylogenetic branch lengths (Q2228245) (← links)
- Estimating drift and minorization coefficients for Gibbs sampling algorithms (Q2239247) (← links)
- A Monte Carlo integration approach to estimating drift and minorization coefficients for Metropolis-Hastings samplers (Q2244839) (← links)
- Approximation and sampling of multivariate probability distributions in the tensor train decomposition (Q2302512) (← links)
- Rademacher complexity for Markov chains: applications to kernel smoothing and Metropolis-Hastings (Q2325397) (← links)
- A Bayesian approach to continuous type principal-agent problems (Q2327651) (← links)
- Convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms (Q2341639) (← links)
- Batch means and spectral variance estimators in Markov chain Monte Carlo (Q2380096) (← links)
- Annealing stochastic approximation Monte Carlo algorithm for neural network training (Q2384162) (← links)
- First hitting time analysis of the independence Metropolis sampler (Q2433963) (← links)
- Remarks on the speed of convergence of mixing coefficients and applications (Q2435775) (← links)
- A central limit theorem for adaptive and interacting Markov chains (Q2448700) (← links)
- Markovian stochastic approximation with expanding projections (Q2448703) (← links)
- Geometric ergodicity for Bayesian shrinkage models (Q2452109) (← links)
- Extremal indices, geometric ergodicity of Markov chains and MCMC (Q2463676) (← links)
- On convergence of properly weighted samples to the target distribution (Q2474400) (← links)
- Attaining the optimal Gaussian diffusion acceleration (Q2511517) (← links)
- Polynomial ergodicity of Markov transition kernels. (Q2574534) (← links)
- A computational procedure for estimation of the mixing time of the random-scan Metropolis algorithm (Q2628881) (← links)
- Exponential concentration inequalities for additive functionals of Markov chains (Q2786488) (← links)
