Pages that link to "Item:Q1613599"
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The following pages link to Geometric ergodicity of Metropolis algorithms (Q1613599):
Displaying 50 items.
- Robust adaptive Metropolis algorithm with coerced acceptance rate (Q116440) (← links)
- Variable transformation to obtain geometric ergodicity in the random-walk Metropolis algorithm (Q139529) (← links)
- Information-geometric Markov chain Monte Carlo methods using diffusions (Q296467) (← links)
- Multiplicative random walk Metropolis-Hastings on the real line (Q356503) (← links)
- Limit theorems for stationary Markov processes with \(L^{2}\)-spectral gap (Q424699) (← links)
- Convergence of adaptive and interacting Markov chain Monte Carlo algorithms (Q449997) (← links)
- Kernel estimators of asymptotic variance for adaptive Markov chain Monte Carlo (Q548543) (← links)
- Limit theorems for some adaptive MCMC algorithms with subgeometric kernels (Q605038) (← links)
- On the ergodicity of the adaptive Metropolis algorithm on unbounded domains (Q614121) (← links)
- On nonlinear Markov chain Monte Carlo (Q638765) (← links)
- On the stability and ergodicity of adaptive scaling Metropolis algorithms (Q645599) (← links)
- On adaptive Markov chain Monte Carlo algorithms (Q817970) (← links)
- On the ergodicity properties of some adaptive MCMC algorithms (Q862214) (← links)
- Geometric ergodicity of a hybrid sampler for Bayesian inference of phylogenetic branch lengths (Q897717) (← links)
- Markov chain Monte Carlo: can we trust the third significant figure? (Q900463) (← links)
- Iterative simulation methods (Q918185) (← links)
- On the validity of the batch quantile method for Markov chains (Q974998) (← links)
- A cautionary tale on the efficiency of some adaptive Monte Carlo schemes (Q988756) (← links)
- Micro-local analysis for the Metropolis algorithm (Q1024207) (← links)
- Geometric convergence of the Metropolis-Hastings simulation algorithm (Q1273019) (← links)
- A note on Metropolis-Hastings kernels for general state spaces (Q1296614) (← links)
- Two convergence properties of hybrid samplers (Q1296738) (← links)
- Geometric ergodicity and hybrid Markov chains (Q1380234) (← links)
- Honest exploration of intractable probability distributions via Markov chain Monte Carlo. (Q1431211) (← links)
- A geometric interpretation of the Metropolis-Hastings algorithm. (Q1431212) (← links)
- \(V\)-subgeometric ergodicity for a Hastings-Metropolis algorithm (Q1587711) (← links)
- Which ergodic averages have finite asymptotic variance? (Q1617127) (← links)
- Quenched phantom distribution functions for Markov chains (Q1640930) (← links)
- Convergent stochastic expectation maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation (Q1663188) (← links)
- On the ergodicity of general mixture of linear autoregressive time series (Q1696088) (← links)
- From Metropolis to diffusions: Gibbs states and optimal scaling. (Q1879490) (← links)
- Practical drift conditions for subgeometric rates of convergence. (Q1879912) (← links)
- Rates of convergence of the Hastings and Metropolis algorithms (Q1922398) (← links)
- Adaptive Gibbs samplers and related MCMC methods (Q1948684) (← links)
- Convergence rate of Markov chain methods for genomic motif discovery (Q1952443) (← links)
- Perturbation bounds for Monte Carlo within metropolis via restricted approximations (Q1986021) (← links)
- Fast mixing of Metropolis-Hastings with unimodal targets (Q1990039) (← links)
- Fourier transform MCMC, heavy-tailed distributions, and geometric ergodicity (Q1998313) (← links)
- Convergence analysis of a collapsed Gibbs sampler for Bayesian vector autoregressions (Q2044318) (← links)
- On the convergence of stochastic approximations under a subgeometric ergodic Markov dynamic (Q2044347) (← links)
- Efficient stochastic optimisation by unadjusted Langevin Monte Carlo. Application to maximum marginal likelihood and empirical Bayesian estimation (Q2058738) (← links)
- A Metropolis-class sampler for targets with non-convex support (Q2058894) (← links)
- On the theoretical properties of the exchange algorithm (Q2137050) (← links)
- Variance bounding of delayed-acceptance kernels (Q2157432) (← links)
- Approximate bounding of mixing time for multiple-step Gibbs samplers (Q2171928) (← links)
- Unbiased Markov chain Monte Carlo for intractable target distributions (Q2192323) (← links)
- Variance reduction for Markov chains with application to MCMC (Q2195839) (← links)
- Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance (Q2196543) (← links)
- Deterministic and stochastic damage detection via dynamic response analysis (Q2206462) (← links)
- A framework for adaptive MCMC targeting multimodal distributions (Q2215766) (← links)
