Subsetting and identification of optimal models in generalized bilinear time series modeling
Joint Authors
Source
Jordan Journal of Mathematics and Statistics
Issue
Vol. 3, Issue 1 (30 Apr. 2010), pp.1-20, 20 p.
Publisher
Yarmouk University Deanship of Research and Graduate Studies
Publication Date
2010-04-30
Country of Publication
Jordan
No. of Pages
20
Main Subjects
Topics
Abstract EN
Significant efforts have been made to study the theory of bilinear time series models, especially simple bilinear (BL) models.
Much less efforts, however, have been made to identify optimal models in generalized bilinear models.
Focus on optimal model identification ; this study attempts to fill this gap.
Full and subset generalized bilinear (SGBL) models are proposed and shown to be robust in achieving stationary for all non-linear series.
The parameters of the proposed models are estimated using robust nonlinear least square method and Newton-Rap son iterative method, and statistical properties of the derived estimates are investigated.
An algorithm is proposed to eliminate redundant parameters from full order generalized bilinear models
American Psychological Association (APA)
Ojo, J. F.& Shangodoyin, D. K.. 2010. Subsetting and identification of optimal models in generalized bilinear time series modeling. Jordan Journal of Mathematics and Statistics،Vol. 3, no. 1, pp.1-20.
https://search.emarefa.net/detail/BIM-266410
Modern Language Association (MLA)
Ojo, J. F.& Shangodoyin, D. K.. Subsetting and identification of optimal models in generalized bilinear time series modeling. Jordan Journal of Mathematics and Statistics Vol. 3, no. 1 (Apr. 2010), pp.1-20.
https://search.emarefa.net/detail/BIM-266410
American Medical Association (AMA)
Ojo, J. F.& Shangodoyin, D. K.. Subsetting and identification of optimal models in generalized bilinear time series modeling. Jordan Journal of Mathematics and Statistics. 2010. Vol. 3, no. 1, pp.1-20.
https://search.emarefa.net/detail/BIM-266410
Data Type
Journal Articles
Language
English
Notes
Includes appendices : p.15
Record ID
BIM-266410