Global convergence conditions in maximum likelihood estimation

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygladolygiad gan gymheiriaid

Fersiynau electronig

Dangosydd eitem ddigidol (DOI)

  • Y. Zou
    Central South University, Changsha
  • W.P. Heath
    University of Manchester
Maximum likelihood estimation has been widely applied in system identification because of consistency, its asymptotic efficiency and sufficiency. However, gradient-based optimisation of the likelihood function might end up in local convergence. In this article we derive various new non-local-minimum conditions in both open and closed-loop system when the noise distribution is a Gaussian process. Here we consider different model structures, in particular ARARMAX, BJ and OE models
Iaith wreiddiolAnadnabyddus
Tudalennau (o-i)475-490
Nifer y tudalennau16
CyfnodolynInternational Journal of Control
Cyfrol85
Rhif y cyfnodolyn5
Dyddiad ar-lein cynnar7 Chwef 2012
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsE-gyhoeddi cyn argraffu - 7 Chwef 2012
Cyhoeddwyd yn allanolIe
Gweld graff cysylltiadau