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• W2111298045 abstract "In this paper we establish the theory of weak convergence (toward a normal distribution) for both single-chain and population stochastic approximation Markov chain Monte Carlo (MCMC) algorithms (SAMCMC algorithms). Based on the theory, we give an explicit ratio of convergence rates for the population SAMCMC algorithm and the single-chain SAMCMC algorithm. Our results provide a theoretic guarantee that the population SAMCMC algorithms are asymptotically more efficient than the single-chain SAMCMC algorithms when the gain factor sequence decreases slower than O (1 / t ), where t indexes the number of iterations. This is of interest for practical applications." @default.
• W2111298045 created "2016-06-24" @default.
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• W2111298045 date "2014-12-01" @default.
• W2111298045 modified "2023-09-23" @default.
• W2111298045 title "Weak Convergence Rates of Population Versus Single-Chain Stochastic Approximation MCMC Algorithms" @default.
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• W2111298045 doi "https://doi.org/10.1239/aap/1418396243" @default.
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