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A sequential empirical CLT for multiple mixing processes with application to $\mathcal{B}$-geometrically ergodic Markov chains

   
@article{EJP3216,
	author = {Herold Dehling and Olivier Durieu and Marco Tusche},
	title = {A sequential empirical CLT for multiple mixing processes with application to $\mathcal{B}$-geometrically ergodic Markov chains},
	journal = {Electron. J. Probab.},
	fjournal = {Electronic Journal of Probability},
	volume = {19},
	year = {2014},
	keywords = {Multivariate Sequential Empirical Processes; Limit Theorems; Multiple Mixing; Spectral Gap; Dynamical Systems; Markov chain;  Change-Point Problems},
	abstract = {We investigate the convergence in distribution of sequential empirical processes of dependent data indexed by a class of functions F. Our technique is suitable for processes that satisfy a multiple mixing condition on a space of functions which differs from the class F. This situation occurs in the case of data arising from dynamical systems or Markov chains, for which the Perron-Frobenius or Markov operator, respectively, has a spectral gap on a restricted space. We provide applications to iterative Lipschitz models that contract on average.},
	pages = {no. 86, 1-26},
	issn = {1083-6489},
	doi = {10.1214/EJP.v19-3216},    
        url = {http://ejp.ejpecp.org/article/view/3216}}