@article{MAKHILLRJAS2007258748,
    title = {Relationship Between an Innovative Outlier Model and the Intervention Effects Model},
    journal = {Research Journal of Applied Sciences},
    volume = {2},
    number = {5},
    pages = {574-578},
    year = {2007},
    issn = {1815-932x},
    doi = {rjasci.2007.574.578},
    url = {https://makhillpublications.co/view-article.php?issn=1815-932x&doi=rjasci.2007.574.578},
    author = {I.U. Moffat and},
    keywords = {ARMA models,estimation,interventions,kalman filters,regression,state space representation,outliers},
    abstract = {We present a relationship between an alternative estimation procedure of ARMA models based on an innovative outlier framework and the Kalman Filter Smoothers (KFS) estimation of intervention effects for outliers generated by special events. The intervention model describes how the events manifest themselves in  the  observations.  The  results  are  asymptotically  equivalent  to the estimation of ARMA parameters based on a generalized t-distribution for the residuals with a  mixture interpretation relying on the innovative outlier  framework.  The   joint   estimation   of  the  estimators, if considered, supports  the  normality test of the residuals.}
    }