Asymptotic Expansion and Conditional Robustness for the Sample Multiple Correlation Coefficient Under Nonnormality

DOI10.1080/03610910500416207zbMath1086.62020OpenAlexW2139774257MaRDI QIDQ3378033

Haruhiko Ogasawara

Publication date: 29 March 2006

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610910500416207

zbMATH Keywords

cumulantsasymptotic biasasymptotic robustnessnonnormalitymultiple correlation coefficient

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Measures of association (correlation, canonical correlation, etc.) (62H20) Robustness and adaptive procedures (parametric inference) (62F35)

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A simple test for zero multiple correlation coefficient in high-dimensional normal data using random projection ⋮ Conservative confidence intervals on multiple correlation coefficient for high-dimensional elliptical data using random projection methodology

Cites Work

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• On the computation of the distribution of the square of the sample multiple correlation coefficient
• On the computation of the noncentral beta distribution
• Asymptotic expansion of the sample correlation coefficient under nonnormality
• Asymptotic biases in exploratory factor analysis and structural equation modeling
• Asymptotic expansions for the distributions of the sample roots under nonnormality
• A Tale of Two Regressions
• The bootstrap and Edgeworth expansion

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