Interacting multiple try algorithms with different proposal distributions
Interacting multiple try algorithms with different proposal distributions
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DOI：
10.1007/s11222-011-9301-9
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发表时间：
2010-11
影响因子：
2.2
通讯作者：
Roberto Casarin;Radu V. Craiu;Fabrizio Leisen
中科院分区：
文献类型：
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作者：
Roberto Casarin;Radu V. Craiu;Fabrizio Leisen
介绍了一类新的交互马尔可夫链蒙特卡罗(MCMC)算法，该算法旨在提高改进的多次尝试Metropolis(MTM)采样器的效率。对现有的MCMC文献的扩展是双重的。大火
We introduce a new class of interacting Markov chain Monte Carlo (MCMC) algorithms which is designed to increase the efficiency of a modified multiple-try Metropolis (MTM) sampler. The extension with respect to the existing MCMC literature is twofold. Fir