A Wavelet Whittle Estimator of the Memory Parameter of a Non-stationary Gaussian Time Series
نویسندگان
چکیده
We consider a time series X = {Xk, k ∈ Z} with memory parameter d0 ∈ 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 d0. 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.
منابع مشابه
A wavelet whittle estimator of the memory parameter of a nonstationaryGaussian time series1]T1
We consider a time series X = {Xk, k ∈ Z} with memory parameter d0 ∈ 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 d0. This is a wavelet-based semiparametric pseudo-likelihood maximum method estimator. The estimator may depend on a given finite range of scales...
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