Nonparametric estimation of the drift coefficient in the diffusion equation
Author:
Pham Dinh Tuan a
| Affiliation: | a Math matiques Appliqu es, Universit de Grenoble, France |
DOI:
10.1080/02331888108801571
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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(English)
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Abstract
A class of nonparametric estimators of the drift coefficient in the Ito diffusion equation, and the related estimators of the nonlinear regression function of a Markov sequence is considered. The estimates are shown to be weakly consistent and asymptotically normal, and estimates at different location points are shown to be asymptotically independent. A study of the asymptotic bias of the estimates is also included.
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| Keywords: Asymptotic normality; diffusion equation; stochastic integrals; recursive estimation; weak consistency |
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