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Central limit approximations for Markov population processes with countably many types

   
@article{EJP1760,
	author = {Andrew Barbour and Malwina Luczak},
	title = {Central limit approximations for Markov population processes with countably many types},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {17},
	year = {2012},
	keywords = {Epidemic models; metapopulation processes; countably many types;  central limit approximation; Markov population processes},
	abstract = {When modelling metapopulation dynamics, the influence of a single patch on the metapopulation depends on the number of individuals in the patch. Since there is usually no obvious natural upper limit on the number of individuals in a patch, this leads to systems in which there are countably infinitely many possible types of entity. Analogous considerations apply in the transmission of parasitic diseases.  In this paper, we prove central limit theorems for quite general systems of this kind, together with bounds on the rate of convergence in an appropriately chosen weighted $\ell_1$ norm.},
	pages = {no. 90, 1-16},
	issn = {1083-6489},
	doi = {10.1214/EJP.v17-1760},    
        url = {http://ejp.ejpecp.org/article/view/1760}}