Scaling phenomena can be found in a variety of physical situations, ranging from applications in hydrology to communication traffic measurements. This paper focuses on quantiles estimation for a self-similar time series and in particular on the uncertainty that affects their estimates. Quantiles provide in fact additional information about the distribution of the measurements and in certain cases they may be of more interest than the mean or variance. Finally, theoretical results will be applied in the estimation of the scaling exponent of a self-similar time series
A stochastic process Y (t) is defined as self-similar with self-similarity parameter H if for any po...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
This paper proposes the cross-quantilogram to measure the quantile dependence between two time serie...
International audienceThis paper is devoted to the introduction of a new class of consistent estimat...
A time-varying quantile can be fitted to a sequence of observations by formulating a time series mod...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
In the last years fractal models have become the focus of many contributions dealing with market dyn...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
We propose a method to analyze a turbulent sequence focusing on the self-similar properties of the d...
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...
The asymptotic behaviour of the quantization errors for self-similar probabilities is determined
A time-varying quantile can be fitted to a sequence of observations by formulating a time series mod...
In this study, we derive the joint asymptotic distributions of functionals of quantile estimators (t...
A new method is proposed to estimate the self-similarity exponent. Instead of applying finite moment...
A stochastic process Y (t) is defined as self-similar with self-similarity parameter H if for any po...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
This paper proposes the cross-quantilogram to measure the quantile dependence between two time serie...
International audienceThis paper is devoted to the introduction of a new class of consistent estimat...
A time-varying quantile can be fitted to a sequence of observations by formulating a time series mod...
Introduction A self-similar process is loosely defined as a stochastic process which generates a sa...
In the last years fractal models have become the focus of many contributions dealing with market dyn...
Introduction A stochastic process Y (t) is defined as self-similar with self-similarity parameter H...
We propose a method to analyze a turbulent sequence focusing on the self-similar properties of the d...
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...
The asymptotic behaviour of the quantization errors for self-similar probabilities is determined
A time-varying quantile can be fitted to a sequence of observations by formulating a time series mod...
In this study, we derive the joint asymptotic distributions of functionals of quantile estimators (t...
A new method is proposed to estimate the self-similarity exponent. Instead of applying finite moment...
A stochastic process Y (t) is defined as self-similar with self-similarity parameter H if for any po...
The purpose of this paper is to study the self-similar properties of discrete-time long memory proce...
This paper proposes the cross-quantilogram to measure the quantile dependence between two time serie...