AbstractIn this paper, we build a central limit theorem for triangular arrays of sequences which satisfy a mild mixing condition. This result allows us to study asymptotic normality of density kernel estimators for some classes of continuous and discrete time processes
The sole purpose of this paper is to establish asymptotic normality of the usual kernel estimate of ...
We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) a...
We establish asymptotic normality of weighted sums of linear processes with general triangular array...
AbstractIn this paper, we build a central limit theorem for triangular arrays of sequences which sat...
In this paper, we study the kernel methods for density estimation of stationary samples under genera...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
AbstractThis article is motivated by a central limit theorem of Ibragimov for strictly stationary ra...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
This paper establishes a central limit theorem (CLT) for empirical processes indexed by smooth funct...
AbstractThis paper studies the asymptotic properties of the kernel probability density estimate of s...
The convergence rates of the sums of -mixing (or strongly mixing) triangular arrays of heterogeneous...
AbstractIn order to construct confidence sets for a marginal density f of a strictly stationary cont...
This paper studies the asymptotic properties of the kernel probability density estimate of stationar...
AbstractIn this paper we prove general statements on the strong convergence of sums of random variab...
In this paper, the central limit theorems for the density estimator and for the integrated square er...
The sole purpose of this paper is to establish asymptotic normality of the usual kernel estimate of ...
We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) a...
We establish asymptotic normality of weighted sums of linear processes with general triangular array...
AbstractIn this paper, we build a central limit theorem for triangular arrays of sequences which sat...
In this paper, we study the kernel methods for density estimation of stationary samples under genera...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
AbstractThis article is motivated by a central limit theorem of Ibragimov for strictly stationary ra...
A central limit theorem is proved for α-mixing random fields. The sets of locations where the random...
This paper establishes a central limit theorem (CLT) for empirical processes indexed by smooth funct...
AbstractThis paper studies the asymptotic properties of the kernel probability density estimate of s...
The convergence rates of the sums of -mixing (or strongly mixing) triangular arrays of heterogeneous...
AbstractIn order to construct confidence sets for a marginal density f of a strictly stationary cont...
This paper studies the asymptotic properties of the kernel probability density estimate of stationar...
AbstractIn this paper we prove general statements on the strong convergence of sums of random variab...
In this paper, the central limit theorems for the density estimator and for the integrated square er...
The sole purpose of this paper is to establish asymptotic normality of the usual kernel estimate of ...
We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) a...
We establish asymptotic normality of weighted sums of linear processes with general triangular array...
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