This study develops two algorithms for the exact sequential updating of the optimal solution for a general discrete-time nonlinear least squares estimation problem as the process length increases and new observations are obtained. One algorithm proceeds via an imbedding on the process length and the final state vector. The second algorithm proceeds via an imbedding on the process length and the final observation vector. Each algorithm generates optimal (least cost) filtered and smoothed state estimates, together with optimal one-step-ahead state predictions. Annotated pointers to related work can be accessed here: http://www.econ.iastate.edu/tesfatsi/flshome.htm
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Publisher Info
Paper provided by Iowa State University, Department of Economics in its series Staff General Research Papers with number
11199.
Length: Date of creation: 11 Jan 2004 Date of revision: Publication status: Published in Nonlinear Analysis, 1988, Vol. 12, pp. 599-615. Handle: RePEc:isu:genres:11199
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Find related papers by JEL classification: B4 - Schools of Economic Thought and Methodology - - Economic Methodology C0 - Mathematical and Quantitative Methods - - General C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General