Weak convergence of multidimensional empirical processes for strong mixing sequences of stochastic vectors
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Publication:4060196
DOI10.1007/BF00538353zbMath0304.60019MaRDI QIDQ4060196
Publication date: 1975
Published in: Zeitschrift für Wahrscheinlichkeitstheorie und verwandte Gebiete (Search for Journal in Brave)
Related Items (13)
Central limit theorems for dependent variables. II ⋮ The blockwise bootstrap for general empirical processes of stationary sequences ⋮ The Bahadur representation of sample quantiles for sequences of strongly mixing random variables ⋮ Bootstrapping the empirical distribution function of a spatial process ⋮ A note on weak convergence of the sequential multivariate empirical process under strong mixing ⋮ Concentration of empirical distribution functions with applications to non-i.i.d. models ⋮ On the Chernoff-Savage theorem for dependent sequences ⋮ Limit theorems for the empirical distribution function in the spatial case. ⋮ A general approach to the joint asymptotic analysis of statistics from sub-samples ⋮ A note on weak convergence of mean residual life of stationary mixing random variables ⋮ One-dimensional empirical measures, order statistics, and Kantorovich transport distances ⋮ Weak convergence of dependent empirical measures with application to subsampling in function spaces ⋮ \(K\)-sample subsampling in general spaces: the case of independent time series
Cites Work
- Weak convergence of multidimensional empirical processes for stationary \(\varphi\)-mixing processes
- A note on empirical processes of strong-mixing sequences
- Convergence of Distributions Generated by Stationary Stochastic Processes
- A Note on Weak Convergence of Empirical Processes for Sequences of $\phi$- Mixing Random Variables
- Convergence Criteria for Multiparameter Stochastic Processes and Some Applications
- Extensions of Billingsley's theorems on weak convergence of empirical processes
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