Asymptotic local test for linearity in adaptive control
This paper deals with an asymptotic local test for linearity of nonlinear dynamical systems. The aim of the test is to compare two estimators of the leading function of the dynamical system, built with the observations contained in a fixed domain . The first one is naturally local since it is a kernel-based estimator. The second one is a -localized version of the least squares estimator. We prove a convergence result, including rate, for the latter estimator and deduce a central limit theorem leading to an asymptotic test. Some simulations illustrate the need of such a local procedure and investigate the finite sample case.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 55 (2001)
Issue (Month): 1 (November)
|Contact details of provider:|| Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/supportfaq.cws_home/regional|
When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:55:y:2001:i:1:p:9-17. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu)
If references are entirely missing, you can add them using this form.