Two sample adaptive rank tests under type II censoring

DOI10.1016/0378-3758(86)90133-3zbMath0584.62063OpenAlexW2042285711MaRDI QIDQ1069598

Konrad Behnen, Georg Neuhaus

Publication date: 1986

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

Full work available at URL: https://doi.org/10.1016/0378-3758(86)90133-3

zbMATH Keywords

Monte Carlo simulationcensored datarank datasmall sample sizesAsymptotic normalityadaptive rank testgeneralized kernel estimatoroptimal nonparametric score functionpower propertiesstochastically larger alternativestwo sample testing problem

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20)

Related Items (1)

Control percentile test procedures for censored data

Cites Work

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• Galton's test as a linear rank test with estimated scores and its local asymptotic efficiency
• Two sample rank estimators of optimal nonparametric score-functions and corresponding adaptive rank statistics
• Asymptotic sufficiency and asymptotically most powerful tests for the two sample consored situation
• A simple algorithm for the adaptation of scores and power behavior of the corresponding rank test
• The randles-hogg test and an alternative proposal
• Asymptotically Most Powerful Rank Tests for the Two-Sample Problem with Censored Data
• Weak Convergence of a Two-sample Empirical Process and a New Approach to Chernoff-Savage Theorems
• Locally Most Powerful Rank Tests for the Two-sample Problem with Censored Data

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