On asymptotic equivalence of the NPMLE of a monotone density and a Grenander-type estimator in multi-sample biased sampling models
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Publication:2044400
DOI10.1214/21-EJS1812zbMath1477.62086OpenAlexW3164370533MaRDI QIDQ2044400
Tony Sit, Kwun Chuen Gary Chan, Sheung Chi Phillip Yam, Hok Kan Ling
Publication date: 9 August 2021
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/21-ejs1812
density estimationKarush-Kuhn-Tucker conditionsasymptotic equivalenceargmax continuous mapping theorem\(s\)-sample biased samplingshape-constrained estimation
Cites Work
- The limit distribution of the \(L_{\infty}\)-error of Grenander-type estimators
- Cube root asymptotics
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- Nonparametric estimation in the presence of length bias
- Estimation of a monotone density in \(s\)-sample biased sampling models
- Weak convergence and empirical processes. With applications to statistics
- The behavior of the NPMLE of a decreasing density near the boundaries of the support
- Likelihood based inference for monotone response models
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- Shape Constrained Non-parametric Estimators of the Baseline Distribution in Cox Proportional Hazards Model
- Nonparametric Estimation under Shape Constraints
- Quantifying the Change of Melanoma Incidence by Breslow Thickness
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- Maximum likelihood estimation in semiparametric selection bias models with application to AIDS vaccine trials
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