𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Efficient On-Line Nonparametric Kernel Density Estimation

✍ Scribed by C. G. Lambert; S. E. Harrington; C. R. Harvey; A. Glodjo

Publisher
Springer
Year
1999
Tongue
English
Weight
152 KB
Volume
25
Category
Article
ISSN
0178-4617

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

The efficiency of bias-corrected estimat
The efficiency of bias-corrected estimators for nonparametric kernel estimation based on local estimating equations
✍ GΓΆran Kauermann; Marlene MΓΌller; Raymond J. Carroll πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 346 KB

for ordinary nonparametric kernel regression and for nonparametric generalized linear model kernel regression constructed estimators with lower order bias than the usual estimators, without the need for devices such as second derivative estimation and multiple bandwidths of different order. We deri

On kernel density estimation near endpoi
On kernel density estimation near endpoints
✍ Shunpu Zhang; Rohana J. Karunamuni πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 144 KB

In this paper, we consider the estimation problem of f(0), the value of density f at the left endpoint 0. Nonparametric estimation of f( 0) is rather formidable due to boundary e ects that occur in nonparametric curve estimation. It is well known that the usual kernel density estimates require modiΓΏ

On the Hilbert kernel density estimate
On the Hilbert kernel density estimate
✍ Luc Devroye; Adam KrzyΕΌak πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 124 KB

Let X be an R d -valued random variable with unknown density f. Let X1; : : : ; Xn be i.i.d. random variables drawn from f. We study the pointwise convergence of a new class of density estimates, of which the most striking member is the Hilbert kernel estimate where V d is the volume of the unit ba