A numerically efficient implementation of the expectation maximization algorithm for state space models
Empirical time series are subject to observational noise. Naïve approaches that estimate parameters in stochastic models for such time series are likely to fail due to the error-in-variables challenge. State space models (SSM) explicitly include observational noise. Applying the expectation maximiza...
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| Published in: | Applied mathematics and computation Vol. 241; pp. 222 - 232 |
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| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Inc
15.08.2014
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| Subjects: | |
| ISSN: | 0096-3003, 1873-5649 |
| Online Access: | Get full text |
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