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A Universally Acceptable Smoothing Factor for Kernel Density Estimates
| Content Provider | Semantic Scholar |
|---|---|
| Author | Devroye, Luc Lugosi, Gábor |
| Abstract | We define a minimum distance estimate of the smoothing factor for kernel density estimates, based upon a methodology first developed by Yatracos (1985). It is shown that if fnh denotes the kernel density estimate on IR d for an i.i.d. sample of size n drawn from an unknown density f , where h is the smoothing factor, and if fn is the kernel estimate with the same kernel and with the proposed new data-based smoothing factor, then, under a regularity condition on the kernel K, sup f lim sup n→∞ E ∫ |fn − f | dx infh>0 E ∫ |fnh − f | dx ≤ 3 . This is the first published smoothing factor that can be proven to have this property. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://luc.devroye.org/DevroyeLugosi-UniversalSmoothing-1996.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Estimated Expanded memory Kernel (operating system) Kernel density estimation Scientific Publication Smoothing (statistical technique) |
| Content Type | Text |
| Resource Type | Article |
