Absolute error criteria for bandwidth selection in density estimation from censored data

DOI10.1080/00949650108812118zbMath1004.62029OpenAlexW2085266145MaRDI QIDQ2784185

W. J. Padgett, J. W. Kuhn, James G. Surles

Publication date: 1 July 2002

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949650108812118

zbMATH Keywords

bandwidth selectionrandom censorshiplifetime datasmoothing parameterasymptotic mean absolute error

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Estimation in survival analysis and censored data (62N02)

Cites Work

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• Asymptotically optimal bandwidth selection for kernel density estimators from randomly right-censored samples
• Kernel density and hazard function estimation in the presence of censoring
• Minimizing \(L_ 1\) distance in nonparametric density estimation
• Strong uniform consistency for nonparametric survival curve estimators from randomly censored data
• Nonparametric Estimation from Incomplete Observations
• Recent Developments in Nonparametric Density Estimation

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