Statistical estimation in partially nonlinear models with random effects
In this article, a partially nonlinear model with random effects is proposed and its new estimation procession is provided. In order to estimate the link function, we propose generalised least square estimate and B-splines estimate methods. Further, we also use the Gauss–Newton method to construct t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2017-07-01
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| Series: | Statistical Theory and Related Fields |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/24754269.2017.1396425 |
| Summary: | In this article, a partially nonlinear model with random effects is proposed and its new estimation procession is provided. In order to estimate the link function, we propose generalised least square estimate and B-splines estimate methods. Further, we also use the Gauss–Newton method to construct the estimates of unknown parameters. Finally, we also consider the estimation for the variance components. The consistency and the asymptotic normality of the estimator will be proved. Simulated and real examples are given to illustrate our proposed methodology, which shows that our methods give effective estimation. |
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| ISSN: | 2475-4269 2475-4277 |