An L1 analysis of a kernel‐based hazard rate estimator

DOI10.1111/ANZS.12224OpenAlexW2791439847MaRDI QIDQ4639814

Prakash N. Patil, Dimitrios Bagkavos, Hairui Hua

Publication date: 11 May 2018

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/anzs.12224

zbMATH Keywords

bandwidthintegrated mean absolute deviation\(L_1\) errorkernel hazard rate

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20)

Cites Work

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• The estimation of the hazard function from randomly censored data by the kernel method
• On the hazard function of Birnbaum-Saunders distribution and associated inference
• The kernel estimate is relatively stable
• Minimizing \(L_ 1\) distance in nonparametric density estimation
• The product-limit estimator and the bootstrap: Some asymptotic representations
• HOW TO OBTAIN BATHTUB-SHAPED FAILURE RATE MODELS FROM NORMAL MIXTURES
• Hazard analysis. I

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