Geometric Ergodicity and Perfect Simulation
نویسندگان
چکیده
منابع مشابه
Geometric Ergodicity and Perfect Simulation
Abstract This note extends the work of Foss and Tweedie (1998), who showed that availability of the classic Propp and Wilson (1996) Coupling from The Past algorithm is essentially equivalent to uniform ergodicity for a Markov chain (see also Hobert and Robert 2004). In this note we show that all geometrically ergodic chains possess dominated Coupling from The Past algorithms (not necessarily pr...
متن کاملGeometric Ergodicity and Hybrid Markov
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 collection of chains commonly used in Markov chain Monte Carlo simulation algorithms, the so-called hybrid chains. We prove that under certain conditions, a hybrid chain will \inherit" the geometric ergo...
متن کاملGeometric Ergodicity of Gibbs Samplers
Due to a demand for reliable methods for exploring intractable probability distributions, the popularity of Markov chain Monte Carlo (MCMC) techniques continues to grow. In any MCMC analysis, the convergence rate of the associated Markov chain is of practical and theoretical importance. A geometrically ergodic chain converges to its target distribution at a geometric rate. In this dissertation,...
متن کاملGeometric Ergodicity and Hybrid Markov Chains
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 collection of chains commonly used in Markov chain Monte Carlo simulation algorithms, the so-called hybrid chains. We prove that under certain conditions, a hybrid chain will “inherit” the geometric ergo...
متن کاملErgodicity breaking in geometric Brownian motion.
Geometric Brownian motion (GBM) is a model for systems as varied as financial instruments and populations. The statistical properties of GBM are complicated by nonergodicity, which can lead to ensemble averages exhibiting exponential growth while any individual trajectory collapses according to its time average. A common tactic for bringing time averages closer to ensemble averages is diversifi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electronic Communications in Probability
سال: 2004
ISSN: 1083-589X
DOI: 10.1214/ecp.v9-1117