Maximum likelihood estimation for Gaussian process with nonlinear drift
We investigate the regression model Xt = θG(t) + Bt, where θ is an unknown parameter, G is a known nonrandom function, and B is a centered Gaussian process. We construct the maximum likelihood estimators of the drift parameter θ based on discrete and continuous observations of the process X and pro...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Vilnius University Press
2018-02-01
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| Series: | Nonlinear Analysis |
| Subjects: | |
| Online Access: | http://www.zurnalai.vu.lt/nonlinear-analysis/article/view/13356 |