Tracking time-varying parameters with local regression |
Alfred Karsten Joensen, Henrik Aalborg Nielsen, Torben Skov Nielsen, Henrik Madsen
|
Abstract | This paper shows that the recursive least-squares (RLS) algorithm with forgetting factor is a special case of a varying-coe$cient model, and a model which can easily be estimated via simple local regression. This observation allows us to formulate a new method which retains the RLS algorithm, but extends the algorithm by including polynomial approximations. Simulation results are provided, which indicates that this new method is superior to the classical RLS method, if the parameter variations are smooth. |
Keywords | Recursive estimation; Varying-coe$cient; Conditional parametric; Polynomial approximation; Weighting functions. |
Type | Journal paper [With referee] |
Journal | Automatica |
Year | 2000 Vol. 36 No. 8 pp. 1199-1204 |
Publisher | Informatics and Mathematical Modelling, Technical University of Denmark, DTU |
Address | Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby |
Electronic version(s) | [pdf] |
BibTeX data | [bibtex] |
IMM Group(s) | Mathematical Statistics |