A rank estimator in the two-sample transformation model with randomly censored data

DOI10.1007/BF00058643zbMath0763.62017OpenAlexW1973728523MaRDI QIDQ1206655

Hideatsu Tsukahara

Publication date: 1 April 1993

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

Full work available at URL: https://doi.org/10.1007/bf00058643

zbMATH Keywords

asymptotic normalityempirical processesrandom censoringasymptotic relative efficiencyright censoringproduct-limit estimatortransformation modelproportional hazards modelcensored data\(M\)-type estimatorgeneralization of Lehmann alternatives modelrandom scores

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Order statistics; empirical distribution functions (62G30)

Related Items (1)

Semiparametric estimation in copula models

Cites Work

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• Rank estimates in a class of semiparametric two-sample models
• Large sample behaviour of the product-limit estimator on the whole line
• Rank regression
• Nonparametric Estimation from Incomplete Observations
• Estimating the Relative Risk with Censored Data
• On estimating equations with censored data
• Estimation of the average hazard ratio
• Partial likelihood
• Weak Convergence of a Two-sample Empirical Process and a New Approach to Chernoff-Savage Theorems
• The Power of Rank Tests
• Robust Statistics

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