A new method is proposed to estimate the self-similarity exponent. Instead of applying finite moment(s) methods, a goodness-of-fit statistic is designed to test whether two rescaled sequences are drawn from the same distribution, which is the definition of self-similarity. The test is the empirical likelihood ratio, which is robust with respect to processes with dependence. We provide a closed formula for fractional Brownian motion and prove that the distance between two rescaled sequences is zero iff the scaling exponent equals the true one. According to our results, the method we propose can identify self-similarity and effectively estimate the corresponding exponent
Self similarity has taken great interest in computer networks since modeling of Ethernet traffic via...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
International audienceThe fractional Brownian motion which has been defined by Kolmogorov \cite{k40}...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
Self-similar stochastic processes are used for stochastic modeling whenever it is expected that long...
on the occasion of his 70th birthday Selfsimilar processes such as fractional Brownian motion are st...
Abstract-The fractional Brownian motion (fBm) model has proven to be valuable in modeling many natur...
Self-similarity, fractal behaviour and long-range dependence are observed in various branches of phy...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
International audienceSelf-similarity has been widely used to model scale-free dynamics, with signif...
Let X be a continuous fractional Brownian motion with parameter of self-similarity H. Let \psi be a ...
In a companion paper (see Self-Similarity: Part I—Splines and Operators), we characterized the class...
The object of this note is to parallel two properties of stochastic processes: self-similarity (ss) ...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
Self similarity has taken great interest in computer networks since modeling of Ethernet traffic via...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
International audienceThe fractional Brownian motion which has been defined by Kolmogorov \cite{k40}...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
In studying the scale invariance of an empirical time series a twofold problem arises: it is necessa...
Self-similar stochastic processes are used for stochastic modeling whenever it is expected that long...
on the occasion of his 70th birthday Selfsimilar processes such as fractional Brownian motion are st...
Abstract-The fractional Brownian motion (fBm) model has proven to be valuable in modeling many natur...
Self-similarity, fractal behaviour and long-range dependence are observed in various branches of phy...
This work is concerned with the analysis of self-similar stochastic pro-cesses, where statistical se...
International audienceSelf-similarity has been widely used to model scale-free dynamics, with signif...
Let X be a continuous fractional Brownian motion with parameter of self-similarity H. Let \psi be a ...
In a companion paper (see Self-Similarity: Part I—Splines and Operators), we characterized the class...
The object of this note is to parallel two properties of stochastic processes: self-similarity (ss) ...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
Self similarity has taken great interest in computer networks since modeling of Ethernet traffic via...
AbstractA self-similar process Z(t) has stationary increments and is invariant in law under the tran...
International audienceThe fractional Brownian motion which has been defined by Kolmogorov \cite{k40}...