𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Nonparametric estimation and prediction for continuous time processes

✍ Scribed by Denis Bosq


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

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Nonparametric estimation equations for t
✍ Zongwu Cai πŸ“‚ Article πŸ“… 2003 πŸ› Elsevier Science 🌐 English βš– 264 KB

In this article, the nonparametric version of estimation equations is investigated, which uniΓΏes various statistical methodologies, for both nonlinear discrete and continuous time series data. The weak consistency and asymptotic normality of the resulting estimators are established. Under this gener

Nonparametric conditional predictive reg
✍ Jan G.De Gooijer; Ali Gannoun πŸ“‚ Article πŸ“… 2000 πŸ› Elsevier Science 🌐 English βš– 371 KB

Several nonparametric predictors based on the Nadaraya-Watson kernel regression estimator have been proposed in the literature. They include the conditional mean, the conditional median, and the conditional mode. In this paper, we consider three types of predictive regions for these predictors -the

An approximated principal component pred
✍ Aguilera, Ana M. ;OcaΓ±a, Francisco A. ;Valderrama, Mariano J. πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 196 KB πŸ‘ 2 views

In this paper, a linear model for forecasting a continuous-time stochastic process in a future interval in terms of its evolution in a past interval is developed. This model is based on linear regression of the principal components in the future against the principal components in the past. In order