A Bahadur efficiency comparison between one and two sample rank statistics and their sequential rank statistic analogues

DOI10.1016/0047-259X(84)90004-6zbMath0535.62043OpenAlexW1988574516MaRDI QIDQ791256

David M. Mason

Publication date: 1984

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0047-259x(84)90004-6

zbMATH Keywords

laws of large numbersBahadur efficiency comparisonone and two sample rank statisticsPitman efficiency against local alternativessequential rank statistic analoguessigned-rank procedures

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Large deviations (60F10) Sequential statistical analysis (62L10)

Related Items (3)

Limit theorems for generalized sequential rank statistics ⋮ On locally most powerful sequential rank tests ⋮ Nonparametric phase-II monitoring for detecting monotone trend based on inverse sampling

Cites Work

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• On the use of a statistic based on sequential ranks to prove limit theorems for simple linear rank statistics
• A nonparametric control chart for detecting small disorders
• A sequential signed-rank test for symmetry
• A condition under which the Pitman and Bahadur approaches to efficiency coincide
• A curious converse of Siever's theorem
• Estimates of location: a large deviation comparison
• A theorem about probabilities of large deviations with an application to queuing theory
• Asymptotic sufficiency of the vector of ranks in the Bahadur sense
• Invariance principles for rank discounted partial sums and averages
• Asymptotically Optimal Tests for Multinomial Distributions
• Alternative Efficiencies for Signed Rank Tests
• On the Probability of Large Deviations and Exact Slopes
• Rates of Convergence of Estimates and Test Statistics
• Large Deviations and Bahadur Efficiency of Linear Rank Statistics
• On Some Convergence Properties of One-Sample Rank Order Statistics
• An Analogue, for Signed Rank Statistics, of Jureckova's Asymptotic Linearity Theorem for Rank Statistics
• On the Limit Behaviour of Extreme Order Statistics

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