Nonstationarity-Extended Local Whittle Estimation

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Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks (2018, methodology): “Using other most updated approaches also based on this technique (e.g., Phillips and Shimotsu, 2004; Abadir et al., 2007) produced essentially the same results.”
Estimators of Long-Memory: Fourier versus Wavelets (2008, methodology): “d is not time-shift invariant, see their Eq. (1). In addition, their estimator is not invariant upon addition of a constant in the data, a drawback which is not easily dealt with, see their Remark 2. Abadir et al. (2007) propose to extend the local Whittle estimator to d∈ (−3/2,∞) calling it the ful”
Persistence in the cryptocurrency market (2017, unknown): “More specifically, we use first the Whittle estimator of d in the frequency domain (Dahlhaus, 1989; Robinson, 1994), and then the “local” Whittle estimator initially proposed by Robinson (1995) and then further developed by Velasco (1999), Phillips and Shimotsu (2005), Abadir et al. (2007) and other”