Add to ORKGCentral limit theorems for integrated squared errors of nonparametric kernel estimators of density and regression functions are established under asymptotic independence conditions as an application of central limit theorems for degenerated U-statistics. These results generalize the corresponding ones obtained by Hall in 1984 in the independence contextAvailable from Departamento de Matematica, Universidade de Coimbra, 3000 Coimbra, Portugal / FCT - Fundação para o Ciência e a TecnologiaSIGLEPTPortuga
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
ABSTRACT. We derive the asymptotic distribution of the integrated square error of a deconvolu-tion k...
This thesis deals with the central limit theorem for dependent random fields and its applications to...
Martingale theory is used to obtain a central limit theorem for degenerate U-statistics with variabl...
Asymmetric kernels are quite useful for the estimation of density functions with bounded support. Ga...
In this paper, we consider the integrated square error where f is the common density function of the...
In this paper we consider the average square error A_n (#pi#)= 1/_n ?"n?_j=_1#left brace#fn(#ch...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
In this paper we consider the weighted average square error An([pi]) = (1/n) [Sigma]nj=1fn(Xj) -; f(...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
In this paper, we establish some new central limit theorems for generalized U-statistics of dependen...
Let Fn be an estimator obtained by integrating a kernel type density estimator based on a random sam...
It has been shown recently that, under an appropriate integra-bility condition, densities of functio...
In this paper we consider a kernel estimator of a density in a convolution model and give a central ...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
ABSTRACT. We derive the asymptotic distribution of the integrated square error of a deconvolu-tion k...
This thesis deals with the central limit theorem for dependent random fields and its applications to...
Martingale theory is used to obtain a central limit theorem for degenerate U-statistics with variabl...
Asymmetric kernels are quite useful for the estimation of density functions with bounded support. Ga...
In this paper, we consider the integrated square error where f is the common density function of the...
In this paper we consider the average square error A_n (#pi#)= 1/_n ?"n?_j=_1#left brace#fn(#ch...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
In this paper we consider the weighted average square error An([pi]) = (1/n) [Sigma]nj=1fn(Xj) -; f(...
Let {Xn, n≥1} be a stationary sequence of associated random variables and Un be a U-statistic ...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
In this paper, we establish some new central limit theorems for generalized U-statistics of dependen...
Let Fn be an estimator obtained by integrating a kernel type density estimator based on a random sam...
It has been shown recently that, under an appropriate integra-bility condition, densities of functio...
In this paper we consider a kernel estimator of a density in a convolution model and give a central ...
AbstractLet F̂n be an estimator obtained by integrating a kernel type density estimator based on a r...
ABSTRACT. We derive the asymptotic distribution of the integrated square error of a deconvolu-tion k...
This thesis deals with the central limit theorem for dependent random fields and its applications to...