AbstractLet {Xi,Yi}i=1∞ be a set of observations from a stationary jointly associated process and θ(x) be the conditional median, that is, θ(x)=inf{y:P(Y⩽y|X=x)⩾12}. We consider the problem of estimating θ(x) based on the L1-norm kernel and establish asymptotic normality of the resulting estimator θn(x)
This paper deals with the problem of estimation of conditional median. The sequence of the nearest n...
AbstractConsider a long term study, where a series of possibly censored failure times is observed. S...
We consider the problem of estimating conditional probability distributions that are multivariate in...
Let be a set of observations from a stationary jointly associated process and [theta](x) be the cond...
The sole purpose of this paper is to establish asymptotic normality of the usual kernel estimate of ...
In this paper, we consider the kernel estimator of the p-dimensional marginal distribution function...
AbstractNonparametric estimation of the conditional mean function for additive models is investigate...
AbstractIn this paper we derive the asymptotic normality and a Berry–Esseen type bound for the kerne...
The main goal of this paper is to study the asymptotic normality of the estimate of the Conditional ...
September 2005; October 2007 (revised)We consider nonparametric estimation of conditional medians fo...
In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship...
Abstract Let us denote by Pd the set of all probability measures on IRd (d ≥ 2), and by M(µ) the set...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
Let fXn; n 1g be a strictly stationary sequence of negatively associated ran-dom variables, with co...
In this paper, we study the kernel methods for density estimation of stationary samples under genera...
This paper deals with the problem of estimation of conditional median. The sequence of the nearest n...
AbstractConsider a long term study, where a series of possibly censored failure times is observed. S...
We consider the problem of estimating conditional probability distributions that are multivariate in...
Let be a set of observations from a stationary jointly associated process and [theta](x) be the cond...
The sole purpose of this paper is to establish asymptotic normality of the usual kernel estimate of ...
In this paper, we consider the kernel estimator of the p-dimensional marginal distribution function...
AbstractNonparametric estimation of the conditional mean function for additive models is investigate...
AbstractIn this paper we derive the asymptotic normality and a Berry–Esseen type bound for the kerne...
The main goal of this paper is to study the asymptotic normality of the estimate of the Conditional ...
September 2005; October 2007 (revised)We consider nonparametric estimation of conditional medians fo...
In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship...
Abstract Let us denote by Pd the set of all probability measures on IRd (d ≥ 2), and by M(µ) the set...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
Let fXn; n 1g be a strictly stationary sequence of negatively associated ran-dom variables, with co...
In this paper, we study the kernel methods for density estimation of stationary samples under genera...
This paper deals with the problem of estimation of conditional median. The sequence of the nearest n...
AbstractConsider a long term study, where a series of possibly censored failure times is observed. S...
We consider the problem of estimating conditional probability distributions that are multivariate in...
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