Rates of Convergence of the Diaconis - Holmes - Neal Markov Chain Sampler with a V-Shaped Stationary Probability
M. Hildebrand
2004, v.10, Issue 4, 687-704
ABSTRACT
The Diaconis - Holmes - Neal Markov chain sampler is a modification of the Metropolis algorithm based on the nearest neighbor random walk. For certain V-shaped stationary probabilities $\pi$ and a choice of a parameter $\theta$, this paper proves that the Diaconis - Holmes - Neal Markov chain approaches its stationary distribution faster than the Markov chain of the corresponding Metropolis algorithm.
Keywords: Metropolis algorithm,Diaconis - Holmes - Neal sampler
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