Moulines, E.; Roueff, F.; Taqqu, M. S. A wavelet Whittle estimator of the memory parameter of a nonstationary Gaussian time series. (English) Zbl 1142.62062 Ann. Stat. 36, No. 4, 1925-1956 (2008). Summary: We consider a time series \(X=\{X_k\), \(k\in \mathbb Z\}\) with memory parameter \(d_{0}\in \mathbb R\). This time series is either stationary or can be made stationary after differencing a finite number of times. We study the “local Whittle wavelet estimator” of the memory parameter \(d_{0}\). This is a wavelet-based semiparametric pseudo-likelihood maximum method estimator. The estimator may depend on a given finite range of scales or on a range which becomes infinite with the sample size. We show that the estimator is consistent and rate optimal if \(X\) is a linear process, and is asymptotically normal if \(X\) is Gaussian. Cited in 1 ReviewCited in 31 Documents MSC: 62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH) 62G05 Nonparametric estimation 42C40 Nontrigonometric harmonic analysis involving wavelets and other special systems 62M15 Inference from stochastic processes and spectral analysis 62G20 Asymptotic properties of nonparametric inference Keywords:long memory; semiparametric estimation; wavelet analysis × Cite Format Result Cite Review PDF Full Text: DOI arXiv References: [1] Abry, P. and Veitch, D. (1998). Wavelet analysis of long-range-dependent traffic. IEEE Trans. Inform. Theory 44 2-15. · Zbl 0905.94006 · doi:10.1109/18.650984 [2] Boyd, S. and Vandenberghe, L. (2004). Convex Optimization . Cambridge Univ. Press. · Zbl 1058.90049 [3] Cohen, A. (2003). Numerical Analysis of Wavelet Methods . North-Holland, Amsterdam. · Zbl 1038.65151 [4] Daubechies, I. (1992). Ten Lectures on Wavelets . SIAM, Philadelphia. · Zbl 0776.42018 [5] Faÿ, G., Roueff, F. and Soulier, P. 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