On estimation of residual moments under koziol-green model of random censorship

DOI10.1080/03610928308831158zbMath0785.62033OpenAlexW1970028182MaRDI QIDQ4275856

Tomáš Herbst

Publication date: 20 January 1994

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928308831158

zbMATH Keywords

proportional hazardssurvival functionrandom censorshipKoziol-Green modelmaximum likelihood estimateSkorokhod spaceindependent competing risksjoint asymptotic distributions of estimated residual momentsweak Gaussian limit

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Non-Markovian processes: estimation (62M09) Inference from stochastic processes (62M99)

Related Items (6)

Nonlinear wavelet density estimation under the Koziol–Green model ⋮ The Paradoxical Nature of The Proportional Hazards Model of Random Censorship ⋮ Distributional convergence under proportional censorship when covariables are present ⋮ Ancillarity properties of generalized residuals with applications in failure time models ⋮ Special issue: Papers from the 7th Eugene Lukacs conference on Mathematical statistics and probability theory. Bowling Green State Univ., Bowling Green, OH, USA, April 25--27, 1997 ⋮ Properties of test statistics applied to residuals in failure time models

Cites Work

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• Large sample behaviour of the product-limit estimator on the whole line
• Large sample theory for an estimator of the mean survival time from censored samples
• Estimation of moments under koziol-green model for random censorship
• A Note on the Weak Convergence of Stochastic Processes
• Nonparametric Estimation from Incomplete Observations
• A note on an estimator of life expectancy with random censorship
• A Review and Critique of Some Models Used in Competing Risk Analysis

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