On convergence rates for quadratic errors in kernel hazard estimation
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Publication:1613073
DOI10.1016/S0167-7152(02)00052-4zbMath0996.62053MaRDI QIDQ1613073
Publication date: 5 September 2002
Published in: Statistics \& Probability Letters (Search for Journal in Brave)
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Estimation in survival analysis and censored data (62N02)
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Cites Work
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- Central limit theorem for integrated square error of multivariate nonparametric density estimators
- Data-driven bandwidth choice for density estimation based on dependent data
- Random approximations to some measures of accuracy in nonparametric curve estimation
- Choice of kernel order in density estimation
- Quadratic errors for nonparametric estimates under dependence
- Mixing: Properties and examples
- Comparison of bandwidth selectors in nonparametric regression under dependence
- A study on bandwidth selection in density estimation under dependence
- Moment bounds for mixing random variables useful in nonparametric function estimation
- Asymptotic behaviors of some measures of accuracy in nonparametric curve estimation with dependent observations
- Asymptotic theory of weakly dependent stochastic processes
- A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
- Recursive probability density estimation for weakly dependent stationary processes
- Nonparametric estimation of the hazard function under dependence conditions
- Hazard analysis. I
- Some New Estimates for Distribution Functions
- Convergence of Distributions Generated by Stationary Stochastic Processes
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