An Empirical Analysis of Some Nonparametric Goodness-of-Fit Tests for Censored Data

DOI10.1080/03610918.2013.796982zbMath1328.62257OpenAlexW2121934680MaRDI QIDQ5259153

M. Vedernikova, Ekaterina V. Chimitova, Narayanaswamy Balakrishnan

Publication date: 24 June 2015

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.796982

zbMATH Keywords

Monte Carlo simulationsgoodness-of-fitAnderson-Darling testempirical powerKolmogorov testNeyman-Pearson testcensored samplesCramer-von Mises-Smirnov testNikulin-Rao-Robson chi-squared testpseudo-complete sample

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10)

Related Items (4)

New characterization-based exponentiality tests for randomly censored data ⋮ Goodness-of-fit tests for the Weibull and extreme value distributions: A review and comparative study ⋮ Goodness-of-fit test for randomly censored data based on maximum correlation ⋮ New classes of tests for the Weibull distribution using Stein's method in the presence of random right censoring

Cites Work

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• Chi-Squared Goodness-of-Fit Tests for Parametric Accelerated Failure Time Models
• Estimation of Hazard, Density and Survivor Functions for Randomly Censored Data
• On Inference in Parametric Survival Data Models

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