Add to ORKGAs an estimator of an estimable parameter, we consider a linear combination of $ mathrm{U}-statistics $ introduced by Toda and Yamato (2001). As a special case, this statistic includes the $ mathrm{V} $-statistic and $ mathrm{LB] $-statistic. In case that the kernel is not degenerate, this linear combination of $ mathrm{U} $-statistics converges to normal distribution. We show some rates of convergence different from Berry-Esseen bound
We specify conditions under which kernel density estimate for linear process is weakly and strongly ...
Rate of convergence to normality for the density estimators of Kernel type is obtained when the obse...
AbstractLet Un be U-statistics based on a symmetric kernel h(x,y) and i.i.d. samples {Xn;n≥1}. In th...
As an estimator of a real estimable parameter, we consider a linear combination of U-statistics whic...
Associated with an estimable parameter, we consider $ mathrm{V} $-statistic and limit of Bayes estim...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
Bentkus V, Götze F. On minimal moment assumptions in Berry-Esseen theorems for U-statistics. THEORY ...
ABSTRACT. Let (X) be a sequence of m-dependent random variables, not necessarily n equally distribut...
Asymptotic expansions for U-statistics and V-statistics with degenerate kernels are investigated, re...
Let {U-n}, n = 1,2,..., be Hilbert space H-valued U-statistics with kernel Phi(.,.), corresponding t...
In this paper we derive almost sure convergence of kernel-type conditional U-statistics in pth mean ...
AbstractIn this paper we derive almost sure convergence of kernel-type conditional U-statistics in p...
The problem of rates of convergence in the strong law of large numbers for degenerate U-statistics i...
AbstractLet Un be a U-statistic based on a symmetric kernel h(x,y) and φ∗-mixing samples {X,Xn;n≥1}....
We specify conditions under which kernel density estimate for linear process is weakly and strongly ...
Rate of convergence to normality for the density estimators of Kernel type is obtained when the obse...
AbstractLet Un be U-statistics based on a symmetric kernel h(x,y) and i.i.d. samples {Xn;n≥1}. In th...
As an estimator of a real estimable parameter, we consider a linear combination of U-statistics whic...
Associated with an estimable parameter, we consider $ mathrm{V} $-statistic and limit of Bayes estim...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
Bentkus V, Götze F. On minimal moment assumptions in Berry-Esseen theorems for U-statistics. THEORY ...
ABSTRACT. Let (X) be a sequence of m-dependent random variables, not necessarily n equally distribut...
Asymptotic expansions for U-statistics and V-statistics with degenerate kernels are investigated, re...
Let {U-n}, n = 1,2,..., be Hilbert space H-valued U-statistics with kernel Phi(.,.), corresponding t...
In this paper we derive almost sure convergence of kernel-type conditional U-statistics in pth mean ...
AbstractIn this paper we derive almost sure convergence of kernel-type conditional U-statistics in p...
The problem of rates of convergence in the strong law of large numbers for degenerate U-statistics i...
AbstractLet Un be a U-statistic based on a symmetric kernel h(x,y) and φ∗-mixing samples {X,Xn;n≥1}....
We specify conditions under which kernel density estimate for linear process is weakly and strongly ...
Rate of convergence to normality for the density estimators of Kernel type is obtained when the obse...
AbstractLet Un be U-statistics based on a symmetric kernel h(x,y) and i.i.d. samples {Xn;n≥1}. In th...