Pages that link to "Item:Q1296614"
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The following pages link to A note on Metropolis-Hastings kernels for general state spaces (Q1296614):
Displaying 50 items.
- Robust Bayesian model selection for heavy-tailed linear regression using finite mixtures (Q2180257) (← links)
- On hitting time, mixing time and geometric interpretations of Metropolis-Hastings reversiblizations (Q2181629) (← links)
- Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance (Q2196543) (← links)
- Markov chain Monte Carlo algorithms with sequential proposals (Q2209708) (← links)
- On the convergence time of some non-reversible Markov chain Monte Carlo methods (Q2218850) (← links)
- Adaptive dimension reduction to accelerate infinite-dimensional geometric Markov chain Monte Carlo (Q2221416) (← links)
- Informed reversible jump algorithms (Q2233560) (← links)
- Counterexamples for optimal scaling of Metropolis-Hastings chains with rough target densities (Q2240841) (← links)
- Proposals which speed up function-space MCMC (Q2252357) (← links)
- Generalized darting Monte Carlo (Q2276015) (← links)
- Metropolis-Hastings reversiblizations of non-reversible Markov chains (Q2289820) (← links)
- Approximation and sampling of multivariate probability distributions in the tensor train decomposition (Q2302512) (← links)
- Non-stationary phase of the MALA algorithm (Q2315120) (← links)
- On the geometric ergodicity of Hamiltonian Monte Carlo (Q2325354) (← links)
- Diffusion limit for the random walk Metropolis algorithm out of stationarity (Q2337836) (← links)
- Convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms (Q2341639) (← links)
- The use of a single pseudo-sample in approximate Bayesian computation (Q2361438) (← links)
- Dimension-independent likelihood-informed MCMC (Q2374891) (← links)
- Elementary bounds on mixing times for decomposable Markov chains (Q2402435) (← links)
- The Wang-Landau algorithm reaches the flat histogram criterion in finite time (Q2443184) (← links)
- Minimising MCMC variance via diffusion limits, with an application to simulated tempering (Q2443188) (← links)
- A central limit theorem for adaptive and interacting Markov chains (Q2448700) (← links)
- A stable manifold MCMC method for high dimensions (Q2453920) (← links)
- Up-and-down experiments of first and second order (Q2485984) (← links)
- On particle Gibbs sampling (Q2515520) (← links)
- Variational principles for asymptotic variance of general Markov processes (Q2690111) (← links)
- Correlation formulas for Markovian network processes in a random environment (Q2806352) (← links)
- Accelerated dimension-independent adaptive metropolis (Q2830629) (← links)
- Dimension-Independent MCMC Sampling for Inverse Problems with Non-Gaussian Priors (Q2945165) (← links)
- Noisy Hamiltonian Monte Carlo for Doubly Intractable Distributions (Q3391199) (← links)
- Statistical Image Analysis for a Confocal Microscopy Two-Dimensional Section of Cartilage Growth (Q3435788) (← links)
- Diffusivity in multiple scattering systems (Q3448982) (← links)
- Impact of Routeing on Correlation Strength in Stationary Queueing Network Processes (Q3535641) (← links)
- Efficiency and Convergence Properties of Slice Samplers (Q4416157) (← links)
- Conductance bounds on the <i>L</i><sup>2</sup> convergence rate of Metropolis algorithms on unbounded state spaces (Q4464174) (← links)
- Comparison of hit-and-run, slice sampler and random walk Metropolis (Q4611278) (← links)
- An Adaptive Independence Sampler MCMC Algorithm for Bayesian Inferences of Functions (Q4641609) (← links)
- Numerical integration using <i>V</i>-uniformly ergodic Markov chains (Q4660534) (← links)
- Bayesian Inference for Non-Gaussian Ornstein–Uhlenbeck Stochastic Volatility Processes (Q4665852) (← links)
- Efficient Construction of Reversible Jump Markov Chain Monte Carlo Proposal Distributions (Q4673751) (← links)
- An Extension of the Metropolis Algorithm (Q4678836) (← links)
- Delayed Acceptance ABC-SMC (Q5066416) (← links)
- Geometric ergodicity of a more efficient conditional Metropolis-Hastings algorithm (Q5079080) (← links)
- Equation-solving estimator based on the general n-step MHDR algorithm (Q5107487) (← links)
- Scalable Optimization-Based Sampling on Function Space (Q5112552) (← links)
- A Bayesian Approach to Estimating Background Flows from a Passive Scalar (Q5119638) (← links)
- Informed Proposals for Local MCMC in Discrete Spaces (Q5130627) (← links)
- Convergence of Conditional Metropolis-Hastings Samplers (Q5169501) (← links)
- Two Metropolis--Hastings Algorithms for Posterior Measures with Non-Gaussian Priors in Infinite Dimensions (Q5237191) (← links)
- Metropolis Integration Schemes for Self-Adjoint Diffusions (Q5250352) (← links)
