A functional central limit theorem for empirical processes under a strong mixing condition

DOI10.1007/s11203-012-9069-3zbMath1253.60049OpenAlexW2013158644MaRDI QIDQ438672

Cristina Tone

Publication date: 31 July 2012

Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11203-012-9069-3

zbMATH Keywords

functional central limit theoremempirical processesrandom fields\(\rho ^{\prime}\)-mixingcontinuous Gaussian process

Mathematics Subject Classification ID

Functional limit theorems; invariance principles (60F17)

Cites Work

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• Recent advances in invariance principles for stationary sequences
• Central limit theorems for empirical measures
• Weak convergence and empirical processes. With applications to statistics
• Central limit theorems for Hilbert-space valued random fields satisfying a strong mixing condition
• On possible mixing rates for some strong mixing conditions for N-tuplewise independent random fields
• Justification and Extension of Doob's Heuristic Approach to the Kolmogorov- Smirnov Theorems
• Convergence of stochastic processes

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