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Spectral bounds for certain two-factor non-reversible MCMC algorithms

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UNIV WASHINGTON, DEPT MATHEMATICS
DOI: 10.1214/ECP.v20-4528

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MCMC algorithm; Gibbs sampler; Metropolis-Hastings algorithm; marginal chain; operator; spectrum; convergence rate; non-reversible

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We prove that the Markov operator corresponding to the two-variable, non-reversible Gibbs sampler has spectrum which is entirely real and non-negative, thus providing a first step towards the spectral analysis of MCMC algorithms in the non-reversible case. We also provide an extension to Metropolis-Hastings components, and connect the spectrum of an algorithm to the spectrum of its marginal chain.

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