Parameter Estimation for Partially Observed Affine and Polynomial Processes
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866909682234294272 |
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| author | Kallsen, Jan Richert, Ivo |
| author_facet | Kallsen, Jan Richert, Ivo |
| contents | This paper is devoted to parameter estimation for partially observed polynomial state space models. This class includes discretely observed affine or more generally polynomial Markov processes. The polynomial structure allows for the explicit computation of a Gaussian quasi-likelihood estimator and its asymptotic covariance matrix. We show consistency and asymptotic normality of the estimating sequence and provide explicitly computable expressions for the corresponding asymptotic covariance matrix. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_05590 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Parameter Estimation for Partially Observed Affine and Polynomial Processes Kallsen, Jan Richert, Ivo Statistics Theory 62M05, 62M12 This paper is devoted to parameter estimation for partially observed polynomial state space models. This class includes discretely observed affine or more generally polynomial Markov processes. The polynomial structure allows for the explicit computation of a Gaussian quasi-likelihood estimator and its asymptotic covariance matrix. We show consistency and asymptotic normality of the estimating sequence and provide explicitly computable expressions for the corresponding asymptotic covariance matrix. |
| title | Parameter Estimation for Partially Observed Affine and Polynomial Processes |
| topic | Statistics Theory 62M05, 62M12 |
| url | https://arxiv.org/abs/2503.05590 |