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On the Geometric Ergodicity of Metropolis-Hastings Algorithms for Lattice Gaussian Sampling
Lattice Gaussian sampling MCMC methods Metropolis-Hastings algorithm
2019/6/10
Sampling from the lattice Gaussian distribution has emerged as an important problem in coding, decoding and cryptography. In this paper, the classic Metropolis-Hastings (MH) algorithm in Markov chain ...
On Geometric Ergodicity of Skewed - SVCHARME models
Markov switching geometric ergodicity irreducibility mixture models asymmetric stochastic volatility
2012/11/23
Markov Chain Monte Carlo is repeatedly used to analyze the properties of intractable distributions in a convenient way. In this paper we derive conditions for geometric ergodicity of a general class o...
Geometric Ergodicity & Scanning Strategies For Two-Component Gibbs Samplers
Geometric Ergodicity Scanning Strategies Two-Component Gibbs Samplers
2012/11/23
In any Markov chain Monte Carlo analysis, rapid convergence of the chain to its target probability distribution is of practical and theoretical importance. A chain that converges at a geometric rate i...
Geometric ergodicity for families of homogeneous Markov chains
Homogeneous Markov chain Geometric ergodicity Couplingrenewal processes Lyapunov function Renewal theory
2010/3/11
In this paper we find nonasymptotic exponential upper bounds for
the deviation in the ergodic theorem for families of homogeneous Markov
processes. We find some sufficient conditions for geometric e...
Various notions of geometric ergodicity for Markov chains on general state spaces exist. In this paper, we review certain relations and implications among them. We then apply these results to a collec...
Geometric Ergodicity and Perfect Simulation
CFTP domCFTP geometric ergodicity perfect simulation uniform ergodicity
2009/4/28
This note extends the work of Foss and Tweedie (1998), who showed that availability of the classic Coupling from the Past (CFTP) algorithm of Propp and Wilson (1996) is essentially equivalent to unifo...