Local bandwidth selection for kernel density estimation from right-censored data based on asymptotic mean absolute error

DOI10.1016/S0362-546X(96)00213-1zbMath1078.62512WikidataQ127172198 ScholiaQ127172198MaRDI QIDQ4378924

W. J. Padgett, J. W. Kuhn

Publication date: 1997

Published in: Nonlinear Analysis: Theory, Methods & Applications (Search for Journal in Brave)

Mathematics Subject Classification ID

Density estimation (62G07)

Related Items (2)

Analysis of strength distributions of multi-modal failures using the EM algorithm ⋮ Bayes bandwidth selection in kernel density estimation with censored data

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
• Smooth nonparametric estimation of the hazard and hazard rate functions from record-breaking data
• Nonparametric Estimation from Incomplete Observations
• Recent Developments in Nonparametric Density Estimation
• On Estimation of a Probability Density Function and Mode

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