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In this paper we consider the problem of measuring stationarity in locally stationary long-memory processes. We introduce an $L_2$-distance between the spectral density of the locally stationary proce...
We introduce the notion of anisotropic long memory for random fields on $\mathbb{Z}^2$ whose partial sums on incommensurate rectangles with sides growing at different rates O(n) and $O(n^{H_1/H_2})$, ...
We consider stationary processes with long memory which are non–Gaussian and represented as Hermite polynomials of a Gaussian process. We focus on the corresponding wavelet coefficients and study th...
We consider the residual empirical process in random design regression with long memory errors. We establish its limiting behaviour, showing that its rates of convergence are different from the rates ...
This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet {\it et al...
The Increment Ratio (IR) statistic was first defined and studied in Surgailis {\it et al.} (2008) for estimating the long-memory parameter either of a stationary or an increment stationary Gaussian p...
We obtain the rate of growth of long strange segments and the rate of decay of infinite horizon ruin probabilities for a class of infinite moving average processes with exponentially light tails. Th...
This paper describes limiting behaviour of tail empirical process associated with long memory stochastic volatility models. We show that such process has dichoto- mous behaviour, according to an int...
We develop a Bayesian procedure for analyzing stationary long-range dependent processes.Specically,we consider the fractional exponential model (FEXP)to estimate the memory parameter of a stationary...
In this paper we investigate the properties of the estimator of degree of differencing the fractional d in long memory time series analysis via consistent spectral density estimation. It is shown t...
Spectral Properties of Temporally Aggregated Long Memory Processes。
We prove that a large set of long memory (LM) processes (including classical LM processes and all processes whose spectral densities have a countable number of singularities controlled by exponential ...
We prove that a large set of long memory (LM) processes (including classical LM processes and all processes whose spectral densities have a countable number of singularities controlled by exponential ...
This work is intended as a contribution to a wavelet-based adaptive estimator of the memory parameter in the classical semi-parametric framework for Gaussian stationary processes. In particular we int...
It is generally accepted that many time series of practical interest exhibit strong dependence, i.e., long memory. For such series, the sample autocorrelations decay slowly and log-log periodogram p...

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