Automatic monitoring and intervention in linear gaussian state-space models: A bayesian approach
Manuel Salvador () and
Additional contact information
Manuel Salvador: Department of Statistical Methods, University of Zaragoza
Pilar Gargallo: Department of Statistical Methods, University of Zaragoza
Documentos de Trabajo from Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza
An automatic monitoring and intervention algorithm that permits the supervision of very general aspects in an univariate linear gaussian state space model is proposed. The algorithm makes use of a model comparison and selection approach within a Bayesian framework. In addition, this algorithm incorporates the possibility of eliminating earlier interventions when subsequent evidence against them comes to light. Finally, the procedure is illustrated with three empirical examples taken from the literature.
Keywords: Bayes Factor; Monitoring and Intervention; Model Comparison; Model Selection; Linear State-Space Models; Kalman Filter (search for similar items in EconPapers)
References: Add references at CitEc
Citations Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: http://EconPapers.repec.org/RePEc:zar:wpaper:dt2003-05
Access Statistics for this paper
More papers in Documentos de Trabajo from Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza Contact information at EDIRC.
Series data maintained by Vicente Pinilla ().