Central limit theorem for sampled sums of dependent random variables
ESAIM: Probability and Statistics, Tome 14 (2010), pp. 299-314
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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 -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
Keywords: random walks, weak dependence, central limit theorem, dynamical systems, random sampling, parametric estimation
Keywords: random walks, weak dependence, central limit theorem, dynamical systems, random sampling, parametric estimation
@article{PS_2010__14__299_0,
author = {Guillotin-Plantard, Nadine and Prieur, Cl\'ementine},
title = {Central limit theorem for sampled sums of dependent random variables},
journal = {ESAIM: Probability and Statistics},
pages = {299--314},
publisher = {EDP-Sciences},
volume = {14},
year = {2010},
doi = {10.1051/ps:2008030},
mrnumber = {2779486},
language = {en},
url = {http://geodesic.mathdoc.fr/articles/10.1051/ps:2008030/}
}
TY - JOUR AU - Guillotin-Plantard, Nadine AU - Prieur, Clémentine TI - Central limit theorem for sampled sums of dependent random variables JO - ESAIM: Probability and Statistics PY - 2010 SP - 299 EP - 314 VL - 14 PB - EDP-Sciences UR - http://geodesic.mathdoc.fr/articles/10.1051/ps:2008030/ DO - 10.1051/ps:2008030 LA - en ID - PS_2010__14__299_0 ER -
%0 Journal Article %A Guillotin-Plantard, Nadine %A Prieur, Clémentine %T Central limit theorem for sampled sums of dependent random variables %J ESAIM: Probability and Statistics %D 2010 %P 299-314 %V 14 %I EDP-Sciences %U http://geodesic.mathdoc.fr/articles/10.1051/ps:2008030/ %R 10.1051/ps:2008030 %G en %F PS_2010__14__299_0
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
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