Testing that marginal sequences of data are not independent via self-normalization

DOI10.1080/02331880601106991zbMath1117.62043OpenAlexW2015624347MaRDI QIDQ3592335

Xin-Xin Jiang

Publication date: 12 September 2007

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880601106991

zbMATH Keywords

central limit theoremself-normalizationexchangeable random variableself-centeringstationary uniform mixing sequence

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Measures of association (correlation, canonical correlation, etc.) (62H20) Stationary stochastic processes (60G10)

Related Items (1)

Testing serial non-independence by self-centring and self-normalizing

Cites Work

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• Self-normalized central limit theorem for sums of weakly dependent random variables
• When is the Student \(t\)-statistic asymptotically standard normal?
• Limit distributions of self-normalized sums
• A Theorem on Products of Random Variables, With Application to Regression
• Parameter Estimates for Symmetric Stable Distributions

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