Computing the nonnull asymptotic variance and the asymptotic relative efficiency of Spearman's rank correlation

DOI10.1016/S0167-9473(01)00081-0zbMath0990.62042MaRDI QIDQ1603896

Craig B. Borkowf

Publication date: 15 July 2002

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

asymptotic relative efficiencyasymptotic varianceSpearman's rank correlationsimulationsempirical distribution functionsFisher's transformation

Mathematics Subject Classification ID

Related Items (10)

Myths About Linear and Monotonic Associations: Pearson’s r, Spearman’s ρ, and Kendall’s τ ⋮ Multivariate extensions of Spearman's rho and related statistics ⋮ Comparison of three semiparametric methods for estimating dependence parameters in copula models ⋮ Linear rank tests for independence in bivariate distributions-power comparisons by simulation ⋮ Detection of block-exchangeable structure in large-scale correlation matrices ⋮ Correlation between graphs with an application to brain network analysis ⋮ Degree-Degree Dependencies in Random Graphs with Heavy-Tailed Degrees ⋮ Tests of Multivariate Independence for Ordinal Data ⋮ Testing independence based on Bernstein empirical copula and copula density ⋮ Influence functions of the Spearman and Kendall correlation measures

Uses Software

• GAUSS

Cites Work

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• A new nonparametric method for variance estimation and confidence interval construction for Spearman's rank correlation.
• TESTS FOR RANK CORRELATION COEFFICIENTS. I
• Analyzing Bivariate Continuous Data Grouped into Categories Defined by Empirical Quantiles of Marginal Distributions
• The variance of Spearman's rho in normal samples
• Asymptotic Expansions for the Moments of the Distribution of Correlation Coefficient
• Rank correlation and product-moment correlation
• RANK AND PRODUCT-MOMENT CORRELATION

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