An invariance principle for triangular arrays of dependent variables with application to autocovariance estimation

DOI10.2307/3315643zbMath0951.62076OpenAlexW2008186358MaRDI QIDQ4267413

Joseph P. Romano, Hui Chen

Publication date: 19 December 1999

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3315643

zbMATH Keywords

invariance principlesmixinglinear processestriangular arraysautocovariance functionsmixingales

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Functional limit theorems; invariance principles (60F17)

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Cites Work

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• Asymptotic normality of spectral estimates
• Time series: theory and methods.
• SPECTRAL ANALYSIS WITH TAPERED DATA
• Conditions for linear processes to be strong-mixing
• Strong invariance principles for triangular arrays of weakly dependent random variables
• Convergence of stochastic processes

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