Long-memory, or more generally fractal, processes are known to play an important role in
many scientific disciplines and applied fields such as physics, geophysics, hydrology …

This paper extends the classical local Whittle estimation procedure of the memory parameter
to fractionally integrated I (d) processes for d∈(-32,∞), covering stationary and …

In this paper, we propose a simple bias–reduced log–periodogram regression estimator,^
dr, of the long–memory parameter, d, that eliminates the first–and higher–order biases of the …

The local Whittle (or Gaussian semiparametric) estimator of long range dependence,
proposed by Künsch (1987) and analyzed by Robinson (1995a), has a relatively slow rate of …

The long-range dependence paradigm appears to be a suitable description of the data
generating process for many observed economic time series. This is mainly due to the fact …

Standard fixed symmetric kernel-type density estimators are known to encounter problems
for positive random variables with a large probability mass close to zero. It is shown that, in …

Semi-parametric estimation methods of the long-memory exponent of a time series have
been studied in several papers, some applied, others theoretical, some using Fourier …

We consider a time series X={X k, k∈ ℤ} with memory parameter d 0∈ ℝ. This time series is
either stationary or can be made stationary after differencing a finite number of times. We …

Metaverse (MV) technology introduces new tools for users each day. MV companies have a
significant share in the total stock markets today, and their size is increasing. However, MV …

This paper studies fractional processes that may be perturbed by weakly dependent time
series. The model for a perturbed fractional process has a components framework in which …