References Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica , 61:821–856. Beran, J., Feng, Y., Ghosh, S., and Kulik, R. (2013). Long memory processes . Springer. Berkes, I., Horv´ ath, L., Kokoszka, P., and Shao, Q.-M. (2006). On discriminating between long- range dependence and changes in mean. Annals of Statistics , 34(3):1140–1165. Betken, A. (2016a). Change point estimation based on Wilcoxon tests in the presence of long- range dependence. arXiv preprint arXiv:1612.08261 . Betken, A. (2016b). Testing for change-points in long-range dependent time series by means of a self-normalized Wilcoxon test. Journal of Time Series Analysis , 20(6):785–809. Billingsley, P. (1968). Convergence of Probability Measures . John Wiley & Sons, Inc. Billingsley, P. (1999). Convergence of Probability Measures . John Wiley & Sons, Inc. Breidt, F. J., Crato, N., and de Lima, P. (1998). The detection and estimation of long memory in stochastic volatility. Journal of Econometrics , 83(1-2):325–348. Cs¨ org¨ o, M. and Horvath, L. (1997). Limit Theorems in Change-Point Analysis . Wiley, New York. De Pooter, M. and Van Dijk, D. (2004). Testing for changes in volatility in heteroskedastic time series – a further examination. Technical report. Dehling, H., Rooch, A., and Taqqu, M. S. (2013). Non-Parametric Change-Point Tests for Long- Range Dependent Data. Scandinavian Journal of Statistics , 40(1):153—173. Dehling, H. and Taqqu, M. (1989). The empirical process of some long-range dependent sequences with an application to U -statistics. The Annals of Statistics , 17(4):1767—1783. Dvoretzky, A. (1972). Asymptotic normality for sums of dependent random variables. Proceedings of the Sixth Berkeley Symposium on Mathematical Statistics and Probability , 2:513–535. Giraitis, L., Leipus, R., and Surgailis, D. (1996). The change-point problem for dependent observations. Journal of Statistical Planning and Inference , 53:297 – 310. Horv´ ath, L. and Kokoszka, P. (1997). The effect of long-range dependence on change-point estimators. Journal of Statistical Planning and Inference , 64(1):57–81. Ivanoff, G. (1983). Stopping times and tightness in two dimensions. Technical Report Series of the Laboratory for Research in Statistics and Probability , 1:46–65. Kulik, R. and Soulier, P. (2011). The tail empirical process for long memory stochastic volatility sequences. Stochastic Processes and their Applications , 121(1):109 – 134. Lobato, I. N. (2001). Testing that a dependent process is uncorrelated. Journal of the American Statistical Association , 96:1066–1076. 53