Free Access
Issue |
ESAIM: PS
Volume 17, 2013
|
|
---|---|---|
Page(s) | 195 - 218 | |
DOI | https://doi.org/10.1051/ps/2011156 | |
Published online | 08 February 2013 |
- R. Adamczak, A tail inequality for suprema of unbounded empirical processes with applications to Markov chains. Electron. J. Probab. 13 (2008) 1000–1034. [CrossRef] [MathSciNet] [Google Scholar]
- K.B. Athreya and P. Ney, A new approach to the limit theory of recurrent Markov chains. Trans. Amer. Math. Soc. 245 (1978) 493–501. [CrossRef] [MathSciNet] [Google Scholar]
- P. Bertail and S. Clémençon, Sharp bounds for the tails of functionals of markov chains, Teor. Veroyatnost. i Primenen 54 (2009) 609–619. [Google Scholar]
- P. Cattiaux and A. Guillin, Deviation bounds for additive functionals of Markov processes. ESAIM : PS 12 (2008) 12–29. [Google Scholar]
- J.-R. Chazottes, P. Collet, C. Külske and F. Redig, Concentration inequalities for random fields via coupling. Probab. Theory Relat. Fields 137 (2007) 201–225. [CrossRef] [Google Scholar]
- S. Clémençon, Moment and probability inequalities for sums of bounded additive functionals of regular Markov chains via the Nummelin splitting technique. Stat. Probab. Lett. 55 (2001) 227–238. [Google Scholar]
- R. Douc, G. Fort and A. Guillin, Subgeometric rates of convergence of f-ergodic strong Markov processes. Stoch. Proc. Appl. 119 (2009) 897–923. [Google Scholar]
- R. Douc, G. Fort, E. Moulines and P. Soulier, Practical drift conditions for subgeometric rates of convergence. Ann. Appl. Probab. 14 (2004) 1353–1377. [CrossRef] [Google Scholar]
- G. Fort and G.O. Roberts, Subgeometric ergodicity of strong Markov processes. Ann. Appl. Probab. 15 (2005) 1565–1589. [CrossRef] [MathSciNet] [Google Scholar]
- A. Guillin, C. Léonard, L. Wu and N. Yao, Transportation-information inequalities for Markov processes. Probab. Theory Relat. Fields 144 (2009) 669–695. [CrossRef] [Google Scholar]
- A.M. Kulik, Exponential ergodicity of the solutions to SDE’s with a jump noise. Stoch. Proc. Appl. 119 (2009) 602–632. [Google Scholar]
- S. Kusuoka and D. Stroock, Applications of the Malliavin calculus. III. J. Fac. Sci., Univ. Tokyo, Sect. I A 34 (1987) 391–442. [Google Scholar]
- R. Höpfner and E. Löcherbach, Limit theorems for null recurrent Markov processes. Memoirs AMS 161 (2003). [Google Scholar]
- P. Lezaud, Chernoff and Berry-Esséen inequalities for Markov processes. ESAIM : PS 5 (2001) 183–201. [Google Scholar]
- E. Löcherbach and D. Loukianova, On Nummelin splitting for continuous time Harris recurrent Markov processes and application to kernel estimation for multi-dimensional diffusions. Stoch. Proc. Appl. 118 (2008) 1301–1321. [Google Scholar]
- E. Löcherbach, D. Loukianova and O. Loukianov, Deviation bounds in ergodic theorem for positively recurrent one-dimensional diffusions and integrability of hitting times. Ann. Inst. Henri Poincaré 47 (2011) 425–449. [CrossRef] [MathSciNet] [Google Scholar]
- E. Nummelin, A splitting technique for Harris recurrent Markov chains. Z. Wahrscheinlichkeitstheorie Verw. Geb. 43 (1978) 309–318. [Google Scholar]
- S. Pal, Concentration for multidimensional diffusions and their boundary local times. To appear in Probab. Theory Relat. Fields (2011), DOI 10.1007/s00440-011-0368-1 [Google Scholar]
- D. Revuz, Markov chains, Revised edition. Amsterdam, North Holland (1984). [Google Scholar]
- E. Rio, Théorie asymptotique des processus aléatoires faiblement dépendants. Springer. Math. Appl. 31 (2000). [Google Scholar]
- T. Simon, Support theorem for jump processes. Stoch. Proc. Appl. 89 (2000) 1–30. [CrossRef] [Google Scholar]
- A.Yu. Veretennikov, On polynomial mixing bounds for stochastic differential equations. Stoch. Proc. Appl. 70 (1997) 115–127. [Google Scholar]
- A.Yu. Veretennikov and S.A. Klokov, On subexponential mixing rate for Markov processes. Teor. Veroyatnost. i Primenen 49 (2004) 21–35. [CrossRef] [Google Scholar]
- L. Wu, A deviation inequality for non-reversible Markov process, Ann. Inst. Henri Poincaré 36 (2000) 435–445. [Google Scholar]
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