Note on the minimum mean integrated squared error of kernel estimates of a distribution function and its derivatives
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Publication:4275170
DOI10.1080/03610929308831040zbMath0798.62049OpenAlexW2038727749MaRDI QIDQ4275170
Publication date: 13 January 1994
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610929308831040
Fourier transformoptimalityderivativesdensity estimationkernel distributionexact expressionParseval's formulaFourier integral estimateminimum integrated squared error
Density estimation (62G07) Fourier and Fourier-Stieltjes transforms and other transforms of Fourier type (42A38)
Related Items (7)
A unified treatment of direct and indirect estimation of a probability density and its derivatives ⋮ Exact mean integrated squared error and bandwidth selection for kernel distribution function estimators ⋮ Nonparametric recursive method for moment generating function kernel-type estimators ⋮ Boundary-free kernel-smoothed goodness-of-fit tests for data on general interval ⋮ Fourier methods for smooth distribution function estimation ⋮ Multistage plug—in bandwidth selection for kernel distribution function estimates ⋮ The law of the iterated logarithm and maximal smoothing principle for the kernel distribution function estimator
Cites Work
- Unnamed Item
- Smooth optimum kernel estimators of densities, regression curves and modes
- Mean integrated square error properties of density estimates
- The performance of kernel density functions in kernel distribution function estimation
- Improvements on strong uniform consistency of some known kernel estimates of a density and its derivatives
- Mean intergrated squared error properties and optimal kernels when estimating a diatribution function
- On the Estimation of the Probability Density, I
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