Kernel estimation of the conditional density under a censorship model
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Publication:1726783
DOI10.1016/J.SPL.2018.09.009zbMath1414.62118OpenAlexW2894886327WikidataQ129139287 ScholiaQ129139287MaRDI QIDQ1726783
Publication date: 20 February 2019
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.spl.2018.09.009
rate of convergencesimulationmean square errorconditional densitycensored datanonparametric estimation
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01)
Related Items (2)
Local linear estimation of the regression function for twice censored data ⋮ Asymptotic properties of a kernel etimate of the conditional mode in the presence of doubly censored data
Cites Work
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- Nonparametric conditional density estimation for censored data based on a recursive kernel
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- Local averaging estimates of the regression function with twice censored data
- Smoothed kernel conditional density estimation
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- Product-limit estimators of the survival function with twice censored data
- Nonparametric functional data analysis. Theory and practice.
- Some asymptotic properties for a smooth kernel estimator of the conditional mode under random censorship
- Bayesian survival estimation for incomplete data when the life distribution is proportionally related to the censoring time
- On Estimation of a Probability Density Function and Mode
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