Nonparametric estimation of density and hazard rate functions with shape restrictions

DOI10.1080/10485252.2010.531133zbMath1359.62416OpenAlexW1977098624MaRDI QIDQ3021201

Mary C. Meyer, Desale Habtzghi

Publication date: 22 July 2011

Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10485252.2010.531133

zbMATH Keywords

right censoringregression splinesmonotone failure rateconvex failure ratedecreasing density

Mathematics Subject Classification ID

Density estimation (62G07) Censored data models (62N01) Reliability and life testing (62N05)

Related Items (7)

Least squares estimation of a \(k\)-monotone density function ⋮ Fusion of hard and soft information in nonparametric density estimation ⋮ One sample goodness of fit tests in presence of shape restrictions on the hazard rate function ⋮ Shape Constrained Kernel PDF and PMF Estimation ⋮ Nonparametric maximum likelihood computation of a \(U\)-shaped hazard function ⋮ Variational analysis of constrained M-estimators ⋮ Semiparametric regression with the U-shaped baseline hazard function in the additive hazards model under general censoring mechanisms

Cites Work

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• Inference using shape-restricted regression splines
• Survival analysis. Techniques for censored and truncated data.
• Computation of nonparametric convex hazard estimators via profile methods
• Consistent maximum likelihood estimation of a unimodal density using shape restrictions
• Hazard Rate Estimation under Random Censoring with Varying Kernels and Bandwidths
• Maximum Likelihood Estimation for Distributions with Monotone Failure Rate
• Properties of Probability Distributions with Monotone Hazard Rate

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