Nonparametric density estimates with improved . performance on given sets of densities
From MaRDI portal
Publication:4207482
DOI10.1080/02331888908802181zbMath0688.62028OpenAlexW2037629246MaRDI QIDQ4207482
Publication date: 1989
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888908802181
rate of convergencerobustnessmodel selectionasymptotic optimalitykernel estimatenormal densitydensity estimatesuniversal consistency
Related Items
Universal smoothing factor selection in density estimation: theory and practice. (With discussion), On quasi-invariant density estimation
Cites Work
- Unnamed Item
- Unnamed Item
- Distribution-free lower bounds in density estimation
- The equivalence of weak, strong, and complete convergence in \(L_ 1\) for kernel density estimates
- Rates of convergence of minimum distance estimators and Kolmogorov's entropy
- The kernel estimate is relatively stable
- Estimating a density under order restrictions: Nonasymptotic minimax risk
- On the risk of histograms for estimating decreasing densities
- Nonparametric maximum likelihood estimation by the method of sieves
- Inequalities for the \(p\)-th moment, \(p\), \(0<p<2\), of a sum of independent random variables
- Minimum Hellinger distance estimates for parametric models
- On estimating a density using Hellinger distance and some other strange facts
- Estimation of a multivariate density
- Remarks on Some Nonparametric Estimates of a Density Function
- A Semiparametric Approach to Density Estimation
- Efficient robust estimates in parametric models
- On arbitrarily slow rates of global convergence in density estimation
- Inequalities for the $r$th Absolute Moment of a Sum of Random Variables, $1 \leqq r \leqq 2$
- On Unbiased Estimation of Density Functions
- On Estimation of a Probability Density Function and Mode
- A Useful Convergence Theorem for Probability Distributions
