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A wavelet Whittle estimator of the memory parameter of a nonstationary Gaussian time series. (English) Zbl 1142.62062

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.

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

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