[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: ::
Back to the articles list Back to browse issues page
Detection of Shocks in Structural Time Series Model Using State Space Forms
Reza Zabihi Moghadam , Rahim Chinipardaz , Gholamali Parham
Abstract:   (124 Views)

In this paper a method has been given to detect the shocks in structural time series using Kalman filter algorithm. As the Kalman filter algorithm is used for state space forms which include ARMA models as an especial case, the suggested method can be used for more general time series than linear models. Five shocks; additive outlier, level change, seasonal change, periodic change and slope change have been reviewed with this method. The performance of suggested method has been shown via a simulation study. The marriage data set from England has been considered as a real data set to study.

Keywords: Kalman filter smoother, Outliers, Structural models, State space model, Structural breaks
Full-Text [PDF 6312 kb]   (426 Downloads)    
Type of Study: Research | Subject: Time Series
Received: 2014/06/12 | Accepted: 2018/04/2 | Published: 2018/04/19
Send email to the article author

Add your comments about this article
Your username or Email:

Write the security code in the box >


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Zabihi Moghadam R, Chinipardaz R, Parham G. Detection of Shocks in Structural Time Series Model Using State Space Forms. J. of Stat. Sci.. 2018; 12 (1)
URL: http://jss.irstat.ir/article-1-303-en.html


Back to the articles list Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
Persian site map - English site map - Created in 0.05 seconds with 31 queries by YEKTAWEB 3647