The accuracy of the binned kernel density estimator is studied for general binning rules. We derive mean squared error results for the closeness of this estimator to both the true density and the unbinned kernel estimator. The binning rule and smoothness of the kernel function are shown to influence
Accuracy of binned kernel functional approximations
✍ Scribed by W. González-Manteiga; C. Sánchez-Sellero; M.P. Wand
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 729 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0167-9473
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
The computational cost of multivariate kernel density estimation can be reduced by prebinning the data. The data are discretized to a grid and a weighted kernel estimator is computed. We report results on the accuracy of such a binned kernel estimator and discuss the computational complexity of the
the DOS of the Holstein t-J model [3], to the dielectric constants of Si quantum dots [4], to linear scaling algo-Chebyshev polynomial approximations are an efficient and numerically stable way to calculate properties of the very large Hamil-rithms for tight-binding molecular dynamics [5], to projec