Uniform \(L_1\)-distance large deviations in nonparametric density estimation
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Publication:2387137
DOI10.1007/BF02595398zbMath1069.62032MaRDI QIDQ2387137
Publication date: 1 September 2005
Published in: Test (Search for Journal in Brave)
Density estimation (62G07) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Large deviations (60F10)
Related Items (3)
Some functional large deviations principles in nonparametric function estimation ⋮ Uniform-in-bandwidth consistency for kernel-type estimators of Shannon's entropy ⋮ Unnamed Item
Cites Work
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- Distribution-free lower bounds in density estimation
- The kernel estimate is relatively stable
- Some nonasymptotic bounds for \(L_ 1\) density estimation using kernels
- On large-deviation efficiency in statistical inference
- A universally acceptable smoothing factor for kernel density estimates
- Nonasymptotic universal smoothing factors, kernel complexity and Yatracos classes
- Large deviations for the \(L_1\)-distance in kernel density estimation
- A minimaxity criterion in nonparametric regression based on large-deviations probabilities
- Weak convergence and empirical processes. With applications to statistics
- [https://portal.mardi4nfdi.de/wiki/Publication:3048064 Estimation des densit�s: risque minimax]
- Large Deviations Limit Theorems for the Kernel Density Estimator
- Asymptotic Efficiency of Nonparametric Tests
- Some Large Deviations Limit Theorems in Conditional Nonparametric Statistics
- Rates of Convergence of Estimates and Test Statistics
- A Useful Convergence Theorem for Probability Distributions
- Large deviations of divergence measures on partitions
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