Dans cet article, nous étudions le théorème central limite conditionnel presque sûr, ainsi que sa forme fonctionnelle, pour des suites stationnaires de variables aléatoires réelles satisfaisant une condition de type projectif. Nous donnons des applications de ces résultats aux processus fortement mélangeants ainsi qu'à des chaînes de Markov nonirréductibles. Les preuves sont essentiellement basées sur une approximation normale de suites doublement indexées de variables aléatoires de type martingale.
In this paper we study the almost sure conditional central limit theorem in its functional form for a class of random variables satisfying a projective criterion. Applications to strongly mixing processes and nonirreducible Markov chains are given. The proofs are based on the normal approximation of double indexed martingale-like sequences, an approach which has interest in itself.
Mots clés : quenched central limit theorem, weak invariance principle, strong mixing, Markov chains
@article{AIHPB_2014__50_3_872_0, author = {Dedecker, J\'er\^ome and Merlev\`ede, Florence and Peligrad, Magda}, title = {A quenched weak invariance principle}, journal = {Annales de l'I.H.P. Probabilit\'es et statistiques}, pages = {872--898}, publisher = {Gauthier-Villars}, volume = {50}, number = {3}, year = {2014}, doi = {10.1214/13-AIHP553}, mrnumber = {3224292}, zbl = {1304.60031}, language = {en}, url = {http://archive.numdam.org/articles/10.1214/13-AIHP553/} }
TY - JOUR AU - Dedecker, Jérôme AU - Merlevède, Florence AU - Peligrad, Magda TI - A quenched weak invariance principle JO - Annales de l'I.H.P. Probabilités et statistiques PY - 2014 SP - 872 EP - 898 VL - 50 IS - 3 PB - Gauthier-Villars UR - http://archive.numdam.org/articles/10.1214/13-AIHP553/ DO - 10.1214/13-AIHP553 LA - en ID - AIHPB_2014__50_3_872_0 ER -
%0 Journal Article %A Dedecker, Jérôme %A Merlevède, Florence %A Peligrad, Magda %T A quenched weak invariance principle %J Annales de l'I.H.P. Probabilités et statistiques %D 2014 %P 872-898 %V 50 %N 3 %I Gauthier-Villars %U http://archive.numdam.org/articles/10.1214/13-AIHP553/ %R 10.1214/13-AIHP553 %G en %F AIHPB_2014__50_3_872_0
Dedecker, Jérôme; Merlevède, Florence; Peligrad, Magda. A quenched weak invariance principle. Annales de l'I.H.P. Probabilités et statistiques, Tome 50 (2014) no. 3, pp. 872-898. doi : 10.1214/13-AIHP553. http://archive.numdam.org/articles/10.1214/13-AIHP553/
[1] Limit Theorems for Functionals of Random Walks. Trudy Mat. Inst. Steklov. 195. Nauka, St. Petersburg, 1994. Transl. into English: Proc. Steklov Inst. Math. 195. Amer. Math. Soc., Providence, RI, 1995. | MR | Zbl
and .[2] On quantiles and the central limit question for strongly mixing sequences. Dedicated to Murray Rosenblatt. J. Theoret. Probab. 10 (1997) 507-555. | MR | Zbl
.[3] Martingale central limit theorems. Ann. Math. Statist. 42 (1971) 59-66. | MR | Zbl
.[4] Limit theorems for functionals of ergodic Markov chains with general state space. Mem. Amer. Math. Soc. 139 (1999) xiv+203. | MR | Zbl
.[5] Pointwise ergodic theorems with rate and application to limit theorems for stationary processes. Stoch. Dyn. 11 (2011) 135-155. | MR | Zbl
.[6] On martingale approximations and the quenched weak invariance principle. Ann. Probab. 42 (2014) 760-793. | MR
and .[7] Central limit theorem started at a point for additive functional of reversible Markov Chains. J. Theoret. Probab. 25 (2012) 171-188. | MR | Zbl
and .[8] A quenched invariance principle for stationary processes. ALEA Lat. Am. J. Probab. Math. Stat. 10 (2013) 107-115. | MR | Zbl
and .[9] Some almost sure results for unbounded functions of intermittent maps and their associated Markov chains. Ann. Inst. Henri Poincaré Probab. Stat. 46 (2010) 796-821. | Numdam | MR | Zbl
, and .[10] Necessary and sufficient conditions for the conditional central limit theorem. Ann. Probab. 30 (2002) 1044-1081. | MR | Zbl
and .[11] On the functional central limit theorem for stationary processes. Ann. Inst. Henri Poincaré Probab. Stat. 36 (2000) 1-34. | Numdam | MR | Zbl
and .[12] The central limit theorem for Markov chains with normal transition operators, started at a point. Probab. Theory Related Fields 119 (2001) 508-528. | MR | Zbl
and .[13] The central limit theorem for Markov chains started at a point. Probab. Theory Related Fields 125 (2003) 73-76. | MR | Zbl
and .[14] The functional central limit theorem for strongly mixing processes. Ann. Inst. Henri Poincaré Probab. Stat. 30 (1994) 63-82. | Numdam | MR | Zbl
, and .[15] Independence of four projective criteria for the weak invariance principle. ALEA Lat. Am. J. Probab. Math. Stat. 5 (2009) 21-26. | MR | Zbl
.[16] Comparison between criteria leading to the weak invariance principle. Ann. Inst. Henri Poincaré Probab. Stat. 44 (2008) 324-340. | Numdam | MR | Zbl
and .[17] On moment conditions for normed sums of independent variables and martingale differences. Stochastic Process. Appl. 19 (1985) 173-182. | MR | Zbl
and .[18] The central limit theorem for stationary processes. Soviet Math. Dokl. 10 (1969) 1174-1176. | MR | Zbl
.[19] Abstracts of communication, T.1: A-K. In International Conference on Probability Theory, Vilnius, 1973.
.[20] The central limit theorem for stationary Markov processes. Soviet Math. Dokl. 19 (1978) 392-394. | MR | Zbl
and .[21] Central limit theorem and stable laws for intermittent maps. Probab. Theory Related Fields 128 (2004) 82-122. | MR | Zbl
.[22] On the departure from normality of a certain class of martingales. Ann. Math. Statist. 41 (1970) 2161-2165. | MR | Zbl
and .[23] Ergodic Theorems. de Gruyter Studies in Mathematics 6. de Gruyter, Berlin, 1985. | MR | Zbl
.[24] Central limit theorem for additive fonctionals of Markov chains. Ann. Probab. 28 (2000) 713-724. | MR | Zbl
and .[25] Recent advances in invariance principles for stationary sequences. Probab. Surv. 3 (2006) 1-36. | MR | Zbl
, and .[26] Almost sure invariance principles via martingale approximation. Stochastic Process. Appl. 122 (2012) 170-190. | MR | Zbl
, and .[27] Strong approximation of partial sums under dependence conditions with application to dynamical systems. Stochastic Process. Appl. 122 (2012) 386-417. | MR | Zbl
and .[28] Markov Chains and Stochastic Stability. Communications and Control Engineering Series. Springer-Verlag, London, 1993. | MR | Zbl
and .[29] Central limit theorem for stationary linear processes. Ann. Probab. 34 (2006) 1608-1622. | MR | Zbl
and .[30] Intermittent transition to turbulence in dissipative dynamical systems. Comm. Math. Phys. 74 (1980) 189-197. | MR | Zbl
and .[31] A central limit theorem and a strong mixing condition. Proc. Natl. Acad. Sci. USA 42 (1956) 43-47. | MR | Zbl
.[32] A weak isomorphism of transformations with invariant measure. Dokl. Akad. Nauk SSSR 147 (1962) 797-800. | MR | Zbl
.[33] On the invariance principle and the law of iterated logarithm for stationary processes. In Mathematical Physics and Stochastic Analysis 424-438. World Sci. Publishing, River Edge, 2000. | MR | Zbl
and .[34] An example of non-quenched convergence in the conditional central limit theorem for partial sums of a linear process. In Dependence in Analysis, Probability and Number Theory (The Phillipp memorial volume) 317-323. Kendrick Press, Heber City, UT, 2010. | MR | Zbl
and .[35] Quenched central limit theorems for sums of stationary processes. Preprint, 2010. Available at arXiv:1006.1795. | MR | Zbl
and .[36] Martingale approximations for sums of stationary processes. Ann. Probab. 32 (2004) 1674-1690. | MR | Zbl
and .[37] Law of the iterated logarithm for stationary processes. Ann. Probab. 36 (2008) 127-142. | MR | Zbl
and .Cité par Sources :