We establish the asymptotic normality of marginal sample quantiles for S–mixing vec-tor stationary processes. S–mixing is a recently introduced and widely applicable notion of dependence. Results of some Monte Carlo simulations are given
International audienceWe present a new technique for proving empirical process invariance principle ...
International audienceThis paper presents different recursive formulas for computing the marginals a...
Extreme value theory for random vectors and stochastic processes with continuous trajectories is usu...
In the study of random processes, dependence is the rule rather than the exception. To facilitate th...
The joint asymptotic distributions of the marginal quantiles and quantile functions in samples from ...
This article considers the problem of testing for symmetry of the marginal distribution of weakly de...
AbstractIt is shown here that Bahadur's [Ann. Math. Statist. (1966) 37, 577–580] almost sure (a.s.) ...
A description of the weak and strong limiting behaviour of weighted uniform tail empirical and tail ...
This paper establishes a central limit theorem (CLT) for empirical processes indexed by smooth funct...
Extreme-value theory for random vectors and stochastic processes with continuous trajectories is usu...
AbstractThe joint asymptotic distributions of the marginal quantiles and quantile functions in sampl...
This thesis is divided in four chapters. The two first chapters introduce a parametric quantile-base...
In this paper, we provide a new method for modelling stationary time series, concentrating on volati...
AbstractBy proving Chibisov-O'Reilly-type theorems for uniform empirical and quantile processes base...
For random vectors taking values in $\mathbb{R}^d$ we introduce a notion of multivariate quantiles d...
International audienceWe present a new technique for proving empirical process invariance principle ...
International audienceThis paper presents different recursive formulas for computing the marginals a...
Extreme value theory for random vectors and stochastic processes with continuous trajectories is usu...
In the study of random processes, dependence is the rule rather than the exception. To facilitate th...
The joint asymptotic distributions of the marginal quantiles and quantile functions in samples from ...
This article considers the problem of testing for symmetry of the marginal distribution of weakly de...
AbstractIt is shown here that Bahadur's [Ann. Math. Statist. (1966) 37, 577–580] almost sure (a.s.) ...
A description of the weak and strong limiting behaviour of weighted uniform tail empirical and tail ...
This paper establishes a central limit theorem (CLT) for empirical processes indexed by smooth funct...
Extreme-value theory for random vectors and stochastic processes with continuous trajectories is usu...
AbstractThe joint asymptotic distributions of the marginal quantiles and quantile functions in sampl...
This thesis is divided in four chapters. The two first chapters introduce a parametric quantile-base...
In this paper, we provide a new method for modelling stationary time series, concentrating on volati...
AbstractBy proving Chibisov-O'Reilly-type theorems for uniform empirical and quantile processes base...
For random vectors taking values in $\mathbb{R}^d$ we introduce a notion of multivariate quantiles d...
International audienceWe present a new technique for proving empirical process invariance principle ...
International audienceThis paper presents different recursive formulas for computing the marginals a...
Extreme value theory for random vectors and stochastic processes with continuous trajectories is usu...
DOI
Add to ORKG