Significance testing of rank cross-correlations between autocorrelated time series with short-range dependence

DOI10.1080/02664763.2022.2137115MaRDI QIDQ6063306

Unnamed Author, Unnamed Author, Unnamed Author, Svenja Fischer

Publication date: 7 November 2023

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

zbMATH Keywords

\(\beta\)-mixingKendall's tauautocorrelationsignificance testingspearman's rho

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Editorial to the special issue: modern streaming data analytics

Cites Work

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• Basic properties of strong mixing conditions. A survey and some open questions
• Mixing properties of ARMA processes
• Time series: theory and methods.
• On measures of association as measures of positive dependence
• Strictly stationary solutions of autoregressive moving average equations
• Some Limit Theorems for Random Functions. II
• Kendall's tau for serial dependence
• Consistency of Kernel Estimators of Heteroscedastic and Autocorrelated Covariance Matrices
• MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS
• Fractional Brownian Motions, Fractional Noises and Applications

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