Estimating Model Variance in the Case of Undermodeling
1992 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 37, no 7, 1004-1008 p.Article in journal (Refereed) Published
A reliable quality estimate of a given model is a prerequisite for any reasonable use of the model. The model error consists of two different contributions: the bias error and the random error. In this contribution, it is shown that the size (variance) of the random error can be reliably estimated in the case where a true system description cannot be achieved in the model structure used. This consistent error estimate can differ considerably from the conventionally used variance estimate, which could thus be misleading.
Place, publisher, year, edition, pages
1992. Vol. 37, no 7, 1004-1008 p.
Modelling, Parameter estimation
IdentifiersURN: urn:nbn:se:liu:diva-95640DOI: 10.1109/9.148358OAI: oai:DiVA.org:liu-95640DiVA: diva2:637089