Nonlinear estimation techniques applied to econometric problems

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Date

2004

Author

Aslan, Serdar

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This thesis considers the filtering and prediction problems of nonlinear noisy econometric systems. As a filter/predictor, the standard tool Extended Kalman Filter and new approaches Discrete Quantization Filter and Sequential Importance Resampling Filter are used. The algorithms are compared by using Monte Carlo Simulation technique. The advantages of the new algorithms over Extended Kalman Filter are shown.

Subject Keywords

Telecommunication.

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http://etd.lib.metu.edu.tr/upload/3/12605649/index.pdf
https://hdl.handle.net/11511/14635

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

S. Aslan, “Nonlinear estimation techniques applied to econometric problems,” M.S. - Master of Science, Middle East Technical University, 2004.