Derivation of a state-space model by functional data analysis (Q1887229)
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scientific article; zbMATH DE number 2118519
| Language | Label | Description | Also known as |
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| English | Derivation of a state-space model by functional data analysis |
scientific article; zbMATH DE number 2118519 |
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Derivation of a state-space model by functional data analysis (English)
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24 November 2004
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A state-space model is proposed for prediction of continuous stochastic processes observed at discrete points. It is based on spline-interpolation of the original process approximated by Karhunen-Loève expansions and Kalman-Bucy filtering techniques. Results of simulations for narrow-band processes and applications to Madrid stock market data are presented.
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spline interpolation
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Kalman filter
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Karhunen-Loève expansion
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