𝔖 Bobbio Scriptorium
✦   LIBER   ✦

An overview of sequential nonparametric density estimation

✍ Scribed by Nitis Mukhopadhyay

Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
552 KB
Volume
30
Category
Article
ISSN
0362-546X

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Nonparametric estimation of density deri
Nonparametric estimation of density derivatives of dependent data
✍ Alejandro Quintela del RΓ­oz πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 742 KB

We study here the kernel type, nonparametric estimation of the derivatives of the density function associated with a strongly mixing time series. The consistency and asymptotic normality properties are studied and a method for the selection of the smoothing parameter by means of the modification of

Nonparametric kernel estimation of an is
Nonparametric kernel estimation of an isotropic variogram
✍ Pilar H. Garcı́a-SoidΓ‘n; Manuel Febrero-Bande; Wenceslao GonzΓ‘lez-Manteiga πŸ“‚ Article πŸ“… 2004 πŸ› Elsevier Science 🌐 English βš– 364 KB

In this paper, we propose nonparametric kernel estimators of the semivariogram, under the assumption of isotropy. At ΓΏrst, a symmetric kernel is considered in order to construct a consistent estimator, so that the selection of the bandwidth parameter is treated via the MSE or the MISE criteria. Next

On a certain class of nonparametric dens
On a certain class of nonparametric density estimators with reduced bias
✍ Kanta Naito πŸ“‚ Article πŸ“… 2001 πŸ› Elsevier Science 🌐 English βš– 113 KB

A class of kernel-based nonparametric density estimators with reduced bias is considered which is constructed from a multiplicative adjustment scheme. Estimators in the class are connected by a real parameter and an interesting fact is that the leading term of the bias is linear in and that of the v