AbstractThe object of the present investigation is to show that the elegant asymptotic almost-sure representation of a sample quantile for independent and identically distributed random variables, established by Bahadur [1] holds for a stationary sequence of φ-mixing random variables. Two different orders of the remainder term, under different φ-mixing conditions, are obtained and used for proving two functional central limit theorems for sample quantiles. It is also shown that the law of iterated logarithm holds for quantiles in stationary φ-mixing processes
Let {}n n NX ∈ be a strictly stationary sequence of ρ−-mixing random variables. We proved the almos...
Let {Xn, n greater than or equal 1} be a sequence of i.i.d. random variables with common d.f. F(x). ...
AbstractLet {Xn} be a strictly stationary φ-mixing process with Σj=1∞ φ12(j) < ∞. It is shown in the...
AbstractThe object of the present investigation is to show that the elegant asymptotic almost-sure r...
AbstractU-quantiles are applied in robust statistics, like the Hodges–Lehmann estimator of location ...
AbstractIt is shown here that Bahadur's [Ann. Math. Statist. (1966) 37, 577–580] almost sure (a.s.) ...
AbstractGiven some regularity conditions on the distribution F(·) of a random X1, ..., Xn emanating ...
An almost sure invariance principle for stationary mixing sequences of random variables with mean ze...
Bahadur representation and its applications have attracted a large number of publications and presen...
We prove the almost sure representation, a law of the iterated logarithm and an invariance principle...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
AbstractAn almost sure invariance principle for stationary mixing sequences of random variables with...
Let $ {(X_i, Y_i) : i = 1, 2, ldots } $ be a sequence of stationary independent random vectors in $ ...
Let {(X1, Y1) : i = 1, 2,...; be a sequence of stationary independent random vectors in:71(2) with a...
Let {}n n NX ∈ be a strictly stationary sequence of ρ−-mixing random variables. We proved the almos...
Let {Xn, n greater than or equal 1} be a sequence of i.i.d. random variables with common d.f. F(x). ...
AbstractLet {Xn} be a strictly stationary φ-mixing process with Σj=1∞ φ12(j) < ∞. It is shown in the...
AbstractThe object of the present investigation is to show that the elegant asymptotic almost-sure r...
AbstractU-quantiles are applied in robust statistics, like the Hodges–Lehmann estimator of location ...
AbstractIt is shown here that Bahadur's [Ann. Math. Statist. (1966) 37, 577–580] almost sure (a.s.) ...
AbstractGiven some regularity conditions on the distribution F(·) of a random X1, ..., Xn emanating ...
An almost sure invariance principle for stationary mixing sequences of random variables with mean ze...
Bahadur representation and its applications have attracted a large number of publications and presen...
We prove the almost sure representation, a law of the iterated logarithm and an invariance principle...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variabl...
AbstractAn almost sure invariance principle for stationary mixing sequences of random variables with...
Let $ {(X_i, Y_i) : i = 1, 2, ldots } $ be a sequence of stationary independent random vectors in $ ...
Let {(X1, Y1) : i = 1, 2,...; be a sequence of stationary independent random vectors in:71(2) with a...
Let {}n n NX ∈ be a strictly stationary sequence of ρ−-mixing random variables. We proved the almos...
Let {Xn, n greater than or equal 1} be a sequence of i.i.d. random variables with common d.f. F(x). ...
AbstractLet {Xn} be a strictly stationary φ-mixing process with Σj=1∞ φ12(j) < ∞. It is shown in the...