Properties of a block bootstrap under long-range dependence
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Adenstedt, R.K. (1974). On large-sample estimation for the mean of a stationary sequence. Ann. Statist., 2, 1095–1107.
Andrews D.W.K. and Sun, Y. (2004). Adaptive local polynomial Whittle estimation of long-range dependence. Econometrica, 72, 569–614.
Andrews, D.W.K., Lieberman, O. and Marmer, V. (2006). Higher-Order Improvements of the Parametric Bootstrap for Long-memory Gaussian processes. J. Econometrics, 133, 673–702.
Beran, J. (1994). Statistical methods for long memory processes. Chapman & Hall, London.
Brockwell, P.J. and Davis, R.A. (1991). Time series: theory and methods. Second Edition, Springer, New York.
Carlstein, E. (1986). The use of subseries methods for estimating the variance of a general statistic from a stationary time series. Ann. Statist., 14, 1171–1179.
Choi, E. and Hall, P. (2000). Bootstrap confidence regions constructed from autoregressions of arbitrary order. J. R. Stat. Soc., Ser. B, 62, 461–477.
Davydov, Y.A. (1970). The invariance principle for stationary processes. Theor. Prob. Appl., 15, 487–498.
Fay, G., Moulines, E. and Soulier, P. (2004). Edgeworth expansions for linear statistics of possibly long-range-dependent linear processes. Statist. Probab. Lett., 66, 275–288.
Geweke, J. and Porter-Hudak, S. (1983). The estimation and application of longmemory time series models. J. Time Series Anal., 4, 221–238.
Giraitis, L., Robinson, P.M. and Surgailis, D. (1999). Variance-type estimation of long memory. Stochastic Process. Appl., 80, 1–24.
Granger, C.W.J. and Joyeux, R. (1980). An introduction to long-memory time series models and fractional differencing. J. Time Series Anal., 1, 15–29.
Hall, P., Horowitz, J.L. and Jing, B.-Y. (1996). On blocking rules for the bootstrap with dependent data. Biometrika, 82, 561–574.
Hall, P., Jing, B.-Y. and Lahiri, S.N. (1998). On the sampling window method for long-range dependent data. Statist. Sinica, 8, 1189–1204.
Hidalgo, J. (2003). An alternative bootstrap to moving blocks for time series regression models. J. Econometrics, 117, 369–399.
Hurvich, C.M., Deo, R. and Brodsky, J. (1998). The mean square error of Geweke and Porter-Hudak’s estimator of the memory parameter of a long memory time series. J. Time Series Anal., 19, 19–46.
Ibragimov, I. A. and Linnik, Y.V. (1971). Independent and stationary sequences of random variables. Wolters-Noordhoff, Groningen.
Kapetanios, G. and Psaradakis, Z. (2006). Sieve bootstrap for strongly dependent stationary processes. Working paper 552, Dept. of Economics, Queen Mary, University of London.
Kreiss, J.P. and Paparoditis, E. (2003). Autogressive aided periodogram bootstrap for time series. Ann. Statist., 31, 1923–1955.
Künsch, H.R. (1987). Statistical aspects of self-similar processes. In Proceedings of the 1st World Congress of the Bernoulli Society, 1, (Yu. A. Prohorov and V. V, Sazanov, eds.), 67–74. VNU Science Press, Utrecht.
Künsch, H.R. (1989). The jackknife and bootstrap for general stationary observations. Ann. Statist., 17, 1217–1261.
Lahiri, S.N. (1993). On the moving block bootstrap under long range dependence. Statist. Probab. Lett., 18, 405–413.
Lahiri, S.N. (1999). Theoretical comparisons of block bootstrap methods. Ann. Statist., 27, 386–404.
Lahiri, S.N., Furukawa, K. and Lee, Y-D. (2007). A nonparametric plug-in rule for selecting optimal block lengths for block bootstrap methods. Stat. Methodol., 4, 292–321.
Liu, R.Y. and Singh, K. (1992). Moving blocks jackknife and bootstrap capture weak dependence. In Exploring the Limits of Bootstrap, (R. LePage and L. Billard, eds.), 225–248. John Wiley & Sons, New York.
Mandelbrot, B.B. and Van Ness, J.W. (1968). Fractional Brownian motions, fractional noises and applications. SIAM Rev., 10, 422–437.
McElroy, T. and Politis, D.N. (2007). Self-normalization for heavy-tailed time series with long memory. Statist. Sinica, 17, 199–220.
Moulines, E. and Soulier, P. (2003). Semiparametric spectral estimation for fractional processes. In P. Doukhan, G. Oppenheim and M. S. Taqqu (eds.), Theory and Applications of Long-range Dependence, (P. Doukhan, G. Oppenheim and M. S. Taqqu, eds.), 251–301. Birkhäuser, Boston.
Nordman, D.J. and Lahiri, S.N. (2005). Validity of the sampling window method for long-range dependent linear processes. Econometric Theory, 21, 1087–1111.
Politis, D.N. and White, H. (2004). Automatic block-length selection for the dependent bootstrap. Econometric Rev., 23, 53–70.
Poskitt, D.S. (2007). Properties of the sieve bootstrap for fractionally integrated and non-invertible processes. J. Time Series Anal., 29, 224–250.
Robinson, P. M. (1995a). Gaussian semiparametric estimation of long range dependence. Ann. Statist., 23, 1630–1661.
Robinson, P. M. (1995b). Log-periodogram regression of time series with long range dependence. Ann. Statist., 23, 1048–1072.