Asymptotic Properties of Just-in-Time Models
1997 (English)In: Proceedings of the 11th IFAC Symposium on System Identification, 1997, 1249-1254 p.Conference paper (Refereed)
The concept of Just-in-Time models has been introduced for models that are not estimated until they are really needed. The prediction is taken as a weighted average of neighboring points in the regressor space, such that an optimal bias/variance trade-off is achieved. The asymptotic properties of the method are investigated, and are compared to the corresponding properties of related statistical non-parametric kernel methods. It is shown that the rate of convergence for Just-in-Time models at least is in the same order as traditional kernel estimators, and that better rates probably can be achieved.
Place, publisher, year, edition, pages
1997. 1249-1254 p.
Non-parametric identification, Nonlinear systems
IdentifiersURN: urn:nbn:se:liu:diva-93788ISBN: 0080425925OAI: oai:DiVA.org:liu-93788DiVA: diva2:628668
11th IFAC Symposium on System Identification, Fukuoka, Japan, July, 1997