Coupling for τ-Dependent Sequences and Applications
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DOI: 10.1007/s10959-004-0578-x
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References listed on IDEAS
- Shao, Qi-Man, 1993. "Almost sure invariance principles for mixing sequences of random variables," Stochastic Processes and their Applications, Elsevier, vol. 48(2), pages 319-334, November.
- Magda Peligrad, 2001. "A Note on the Uniform Laws for Dependent Processes Via Coupling," Journal of Theoretical Probability, Springer, vol. 14(4), pages 979-988, October.
- Peligrad, Magda, 2002. "Some remarks on coupling of dependent random variables," Statistics & Probability Letters, Elsevier, vol. 60(2), pages 201-209, November.
- Jerôme Dedecker & Paul Doukhan, 2002. "A New Covariance Inequality and Applications," Working Papers 2002-25, Center for Research in Economics and Statistics.
- Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
- Major, Péter, 1978. "On the invariance principle for sums of independent identically distributed random variables," Journal of Multivariate Analysis, Elsevier, vol. 8(4), pages 487-517, December.
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- Xu, Haotian & Wang, Daren & Zhao, Zifeng & Yu, Yi, 2022. "Change point inference in high-dimensional regression models under temporal dependence," LIDAM Discussion Papers ISBA 2022027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Demian Pouzo, 2024. "Maximal Inequalities for Empirical Processes under General Mixing Conditions with an Application to Strong Approximations," Papers 2402.11394, arXiv.org, revised Apr 2024.
- Fang Han & Yicheng Li, 2020. "Moment Bounds for Large Autocovariance Matrices Under Dependence," Journal of Theoretical Probability, Springer, vol. 33(3), pages 1445-1492, September.
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Keywords
Coupling; dependent sequences; Bernoulli shifts; Markov chains; exponential inequalities; strong invariance principle; law of the iterated logarithm;All these keywords.
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