Robust rank tests for \(k\)-sample approximate equality in the presence of gross errors

DOI10.1016/S0378-3758(00)00170-1zbMath0965.62039MaRDI QIDQ5931391

Itsuro Kakiuchi, Miyoshi Kimura

Publication date: 31 July 2001

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

Schur-concave functionasymptotic relative efficiencyasymptotic maximum sizeasymptotic minimum powergross error neighborhoodk-sample approximate equalityk-sample rank testmarjorizationSchur-convex set

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35)

Related Items (2)

Majorization methods on hyperplanes and their applications ⋮ Robust slippage rank tests for \(k\) location parameters in the presence of gross errors

Cites Work

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• A majorization inequality for distributions on hyperplanes and its applications to tests for outliers
• Robustness of one- and two-sample rank tests against gross errors
• Least favorable pairs for special capacities
• A robust asymptotic testing model
• Majorization methods on hyperplanes and their applications
• On the centering of a simple linear rank statistic
• Asymptotic Normality of Simple Linear Rank Statistics Under Alternatives
• Inequalities: theory of majorization and its applications

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