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A Functional Central Limit Theorem for a Class of Interacting Markov Chain Monte Carlo Methods

   
@article{EJP701,
	author = {Bernard Bercu and Pierre Del Moral and Arnaud Doucet},
	title = {A Functional Central Limit Theorem for a Class of Interacting Markov Chain Monte Carlo Methods},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {14},
	year = {2009},
	keywords = {Multivariate and functional central limit theorems, random fields, martingale limit theorems, self-interacting Markov chains, Markov chain Monte Carlo methods, Feynman-Kac semigroups},
	abstract = {We present a functional central limit theorem for a new class of interacting Markov chain Monte Carlo algorithms. These stochastic algorithms have been recently introduced to solve non-linear measure-valued equations. We provide an original theoretical analysis based on semigroup techniques on distribution spaces and fluctuation theorems for self-interacting random fields. Additionally we also present a series of sharp mean error bounds in terms of the semigroup associated with the first order expansion of the limiting measure-valued process. We illustrate our results in the context of Feynman-Kac semigroups},
	pages = {no. 73, 2130-2155},
	issn = {1083-6489},
	doi = {10.1214/EJP.v14-701},    
        url = {http://ejp.ejpecp.org/article/view/701}}