AbstractU-quantiles are applied in robust statistics, like the Hodges–Lehmann estimator of location for example. They have been analysed in the case of independent random variables with the help of a generalized Bahadur representation. Our main aim is to extend these results to U-quantiles of strongly mixing random variables and functionals of absolutely regular sequences. We obtain the central limit theorem and the law of the iterated logarithm for U-quantiles as straightforward corollaries. Furthermore, we improve the existing result for sample quantiles of mixing data
In this paper, we consider U-statistics whose data is a strictly stationary sequence which can be ex...
AbstractFor a sequence of φ-mixing Rd-valued random vectors {Xn,n⩾1}, based on the Berkes–Philipp co...
Bahadur representation and its applications have attracted a large number of publications and presen...
AbstractU-quantiles are applied in robust statistics, like the Hodges–Lehmann estimator of location ...
AbstractThe object of the present investigation is to show that the elegant asymptotic almost-sure r...
International audienceLet (X i) i≥1 be a sequence of strong-mixing random variables with common unkn...
Generalized linear statistics are a unifying class that contains U-statistics, U-quantiles, L-stati...
AbstractGeneralized linear statistics are a unifying class that contains U-statistics, U-quantiles, ...
AbstractIn this paper, the Berry–Esséen bound of sample quantiles for φ-mixing random variables is i...
Cataloged from PDF version of article.Suppose that we observe bivariate data (X,. q) only when Y, < ...
AbstractW. Stute (Ann. Probab.19,No. 2 (1991), 812–825) introduced a class of so-calledU-statistics,...
AbstractLet {Xn} be a strictly stationary φ-mixing process with Σj=1∞ φ12(j) < ∞. It is shown in the...
We will show under minimal conditions on differentiability and dependence that the central limit th...
We define a time dependent empirical process based on n independent fractional Brownian motions and ...
AbstractWe consider a conditional empirical distribution of the form Fn(C∣x)=∑nt=1ωn(Xt−x)I{Yt∈C} in...
In this paper, we consider U-statistics whose data is a strictly stationary sequence which can be ex...
AbstractFor a sequence of φ-mixing Rd-valued random vectors {Xn,n⩾1}, based on the Berkes–Philipp co...
Bahadur representation and its applications have attracted a large number of publications and presen...
AbstractU-quantiles are applied in robust statistics, like the Hodges–Lehmann estimator of location ...
AbstractThe object of the present investigation is to show that the elegant asymptotic almost-sure r...
International audienceLet (X i) i≥1 be a sequence of strong-mixing random variables with common unkn...
Generalized linear statistics are a unifying class that contains U-statistics, U-quantiles, L-stati...
AbstractGeneralized linear statistics are a unifying class that contains U-statistics, U-quantiles, ...
AbstractIn this paper, the Berry–Esséen bound of sample quantiles for φ-mixing random variables is i...
Cataloged from PDF version of article.Suppose that we observe bivariate data (X,. q) only when Y, < ...
AbstractW. Stute (Ann. Probab.19,No. 2 (1991), 812–825) introduced a class of so-calledU-statistics,...
AbstractLet {Xn} be a strictly stationary φ-mixing process with Σj=1∞ φ12(j) < ∞. It is shown in the...
We will show under minimal conditions on differentiability and dependence that the central limit th...
We define a time dependent empirical process based on n independent fractional Brownian motions and ...
AbstractWe consider a conditional empirical distribution of the form Fn(C∣x)=∑nt=1ωn(Xt−x)I{Yt∈C} in...
In this paper, we consider U-statistics whose data is a strictly stationary sequence which can be ex...
AbstractFor a sequence of φ-mixing Rd-valued random vectors {Xn,n⩾1}, based on the Berkes–Philipp co...
Bahadur representation and its applications have attracted a large number of publications and presen...