AbstractLet {Xn, n ≥ 1} be a stationary sequence of ρ-mixing random variables satisfying EXn = μ, EX2n < ∞, Var Sn/n → σ2 > 0. This paper presents a class of estimators of σ and investigates their weak consistency as well as their asymptotic normality. Applications to the self-normalizing central limit theorem and confidence for the sample mean are also discussed
In this article we give a necessary and sufficient condition for a self-normalized weak invariance p...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
Although robust estimation methods were formalized by the late 1800s, data trimming and truncation f...
Let {}n n NX ∈ be a strictly stationary sequence of ρ−-mixing random variables. We proved the almos...
Abstract Let {X,Xn}n∈N $\{X, X_{n}\}_{n\in N}$ be a strictly stationary ρ− $\rho^{-}$-mixing sequenc...
Let Xn, n [greater-or-equal, slanted] 1 be a stationary sequence of associated random variables sati...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...
AbstractLet Xn, n ⩾ 1 be a stationary sequence of associated random variables satisfying E(X1) = μ, ...
AbstractLet X1,X2,… be a strictly stationary sequence of ρ-mixing random variables with mean zeros a...
Let $X_1,X_2,\ldots$ be a centred sequence of weakly stationary random variables with spectral measu...
AbstractLet {Xi,i≥1} be a sequence of i.i.d. random variables which is in the domain of attraction o...
In this paper we extend a theorem of Bradley under interlaced mixing and strong mixing conditions. M...
AbstractIn a sample X1,…,XN, independently and identically distributed with distribution F, a linear...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
AbstractIn this paper we prove general statements on the strong convergence of sums of random variab...
In this article we give a necessary and sufficient condition for a self-normalized weak invariance p...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
Although robust estimation methods were formalized by the late 1800s, data trimming and truncation f...
Let {}n n NX ∈ be a strictly stationary sequence of ρ−-mixing random variables. We proved the almos...
Abstract Let {X,Xn}n∈N $\{X, X_{n}\}_{n\in N}$ be a strictly stationary ρ− $\rho^{-}$-mixing sequenc...
Let Xn, n [greater-or-equal, slanted] 1 be a stationary sequence of associated random variables sati...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...
AbstractLet Xn, n ⩾ 1 be a stationary sequence of associated random variables satisfying E(X1) = μ, ...
AbstractLet X1,X2,… be a strictly stationary sequence of ρ-mixing random variables with mean zeros a...
Let $X_1,X_2,\ldots$ be a centred sequence of weakly stationary random variables with spectral measu...
AbstractLet {Xi,i≥1} be a sequence of i.i.d. random variables which is in the domain of attraction o...
In this paper we extend a theorem of Bradley under interlaced mixing and strong mixing conditions. M...
AbstractIn a sample X1,…,XN, independently and identically distributed with distribution F, a linear...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
AbstractIn this paper we prove general statements on the strong convergence of sums of random variab...
In this article we give a necessary and sufficient condition for a self-normalized weak invariance p...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
Although robust estimation methods were formalized by the late 1800s, data trimming and truncation f...