𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Classification procedures using multivariate variable kernel density estimate

✍ Scribed by Adam Krzyzak


Publisher
Elsevier Science
Year
1983
Tongue
English
Weight
334 KB
Volume
1
Category
Article
ISSN
0167-8655

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Multivariate Statistical Process Monitor
✍ Liang, J. πŸ“‚ Article πŸ“… 2008 πŸ› Curtin University of Technology 🌐 English βš– 426 KB πŸ‘ 1 views

## Abstract In this paper, a general kernel density estimator has been introduced and discussed for multivariate processes in order to provide enhanced real‐time performance monitoring. The proposed approach is based upon the concept of kernel density function, which is more appropriate to the unde

Pointwise Improvement of Multivariate Ke
✍ Belkacem Abdous; Alain Berlinet πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 428 KB

Multivariate kernel density estimators are known to systematically deviate from the true value near critical points of the density surface. To overcome this difficulty a method based on Rao Blackwell's theorem is proposed. Local corrections of kernel density estimators are achieved by conditioning t

Multivariate Density Estimation with Gen
✍ Dimitris N. Politis; Joseph P. Romano πŸ“‚ Article πŸ“… 1999 πŸ› Elsevier Science 🌐 English βš– 430 KB

The problem of nonparametric estimation of a multivariate density function is addressed. In particular, a general class of estimators with favorable asymptotic performance (bias, variance, rate of convergence) is proposed. The proposed estimators are characterized by the flatness near the origin of