Asymptotic Performance Bounds for the Kernel Estimate
Devroye, Luc
Ann. Statist., Tome 16 (1988) no. 1, p. 1162-1179 / Harvested from Project Euclid
We consider an arbitrary sequence of kernel density estimates $f_n$ with kernels $K_n$ possibly depending upon $n$. Under a mild restriction on the sequence $K_n$, we obtain inequalities of the type $E\big(\int|f_n - f|\big) \geq (1 + o(1))\Psi(n, f),$ where $f$ is the density being estimated and $\Psi(n, f)$ is a function of $n$ and $f$ only. The function $\psi$ can be considered as an indicator of the difficulty of estimating $f$ with any kernel estimate.
Publié le : 1988-09-14
Classification:  Density estimation,  $L_1$ error,  inequalities,  characteristic function,  kernel estimate,  performance bounds,  60E15,  62G05
@article{1176350953,
     author = {Devroye, Luc},
     title = {Asymptotic Performance Bounds for the Kernel Estimate},
     journal = {Ann. Statist.},
     volume = {16},
     number = {1},
     year = {1988},
     pages = { 1162-1179},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176350953}
}
Devroye, Luc. Asymptotic Performance Bounds for the Kernel Estimate. Ann. Statist., Tome 16 (1988) no. 1, pp.  1162-1179. http://gdmltest.u-ga.fr/item/1176350953/