The convergence rate of the Gibbs sampler for generalized 1-D Ising model
classification
🧮 math.PR
cond-mat.stat-mech
keywords
boundisingmodelbetaconvergencegeneralizedgibbsone-dimensional
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The rate of convergence of the Gibbs sampler for the generalized one-dimensional Ising model is determined by the second largest eigenvalue of its transition matrix in absolute value denoted by $\beta^*$. In this paper we generalize a result from Shiu and Chen $(2015)$ for the one-dimensional Ising model with two states which gives a bound for $\beta^*$ . The method is based on Diaconis and Stroock bound for reversible Markov processes. The new bound presented in this paper improves Ingrassia's $(1994)$ result.
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