A two-stage rank test using density estimation

DOI10.1007/BF01856541zbMath0843.62051OpenAlexW2056935428MaRDI QIDQ1915251

Willem Albers

Publication date: 16 June 1996

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01856541

zbMATH Keywords

tablesasymptotic expansionslocal alternativeone-sample problemStein's two-stage procedureWilcoxon scoresdensity derivativesintegrated squared densitiesrequired powertwo-stage rank test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10)

Cites Work

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• Achieving information bounds in non and semiparametric models
• Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives
• The robustness of Stein's two-stage procedure
• Second order analysis of two-stage rank tests for the one-sample problem
• An exact rank test for scale under normality using Helmert's transformation
• Estimation of integrated squared density derivatives
• Geometrizing rates of convergence. II
• Asymptotic expansions for two-stage rank tests
• Optimal plug-in estimators for nonparametric functional estimation
• Asymptotic expansions for the power of distribution free tests in the one-sample problem
• Estimating densities, quantiles, quantile densities and density quantiles
• Sequential rank tests for location
• On Bounded Length Sequential Confidence Intervals Based on One-Sample Rank Order Statistics

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