Estimating the Variance in Case of Undermodeling Using Bootstrap
1999 (English)In: Proceedings of the 38th IEEE Conference on Decision and Control, 1999, 2394-2399 vol.3 p.Conference paper (Refereed)
Simulation based methods have gained interest in the signal processing community. In this article we propose an algorithm to estimate the probability density function of some statistic associated with an identified model in the case of undermodeling. With this algorithm, we are thus able to estimate the variance error of any statistic associated with the model. We also give a simulation example, which shows that the estimates are in very good agreement with Monte Carlo simulations.
Place, publisher, year, edition, pages
1999. 2394-2399 vol.3 p.
Bootstrap, Identification, Model uncertainty, Undermodeling
IdentifiersURN: urn:nbn:se:liu:diva-94080DOI: 10.1109/CDC.1999.831283ISBN: 0-7803-5250-5OAI: oai:DiVA.org:liu-94080DiVA: diva2:629108
38th IEEE Conference on Decision and Control, Phoenix, AZ, USA, December, 1999