Empirical process theory for nonsmooth functions under functional dependence
Author:
Affiliation:
1. Institut für angewandte Mathematik, Im Neuenheimer Feld 205, Universität Heidelberg
Publisher
Institute of Mathematical Statistics
Subject
Statistics and Probability,Statistics, Probability and Uncertainty
Reference22 articles.
1. Zhang, D. and Wu, W. B. (2017). Gaussian approximation for high dimensional time series. Ann. Statist. 45 1895–1919.
2. Borovkova, S., Burton, R. and Dehling, H. (2001). Limit theorems for functionals of mixing processes with applications to U-statistics and dimension estimation. Trans. Amer. Math. Soc. 353 4261–4318.
3. AKRITAS, M. G. and VAN KEILEGOM, I. (2001). Non-parametric estimation of the residual distribution. Scand. J. Statist. 28 549–567.
4. ARCONES, M. A. and YU, B. (1994). Central limit theorems for empirical and U-processes of stationary mixing sequences. J. Theoret. Probab. 7 47–71.
5. BERKES, I., HÖRMANN, S. and SCHAUER, J. (2009). Asymptotic results for the empirical process of stationary sequences. Stochastic Process. Appl. 119 1298–1324.
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