Central limit theorem for sampled sums of dependent random variables
ESAIM: Probability and Statistics, Tome 14 (2010), pp. 299-314.

We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to dependent random variables sampled by a ℤ-valued transient random walk. This extends the results obtained by [N. Guillotin-Plantard and D. Schneider, Stoch. Dynamics 3 (2003) 477-497]. An application to parametric estimation by random sampling is also provided.

DOI : 10.1051/ps:2008030
Classification : Primary 60F05, 60G50, 62D05, Secondary 37C30, 37E05
Mots-clés : random walks, weak dependence, central limit theorem, dynamical systems, random sampling, parametric estimation 
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     title = {Central limit theorem for sampled sums of dependent random variables},
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     pages = {299--314},
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     doi = {10.1051/ps:2008030},
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     language = {en},
     url = {http://archive.numdam.org/articles/10.1051/ps:2008030/}
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Guillotin-Plantard, Nadine; Prieur, Clémentine. Central limit theorem for sampled sums of dependent random variables. ESAIM: Probability and Statistics, Tome 14 (2010), pp. 299-314. doi : 10.1051/ps:2008030. http://archive.numdam.org/articles/10.1051/ps:2008030/

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