Abstract
In time series analyses and forecasting, dynamic linear models of canonical form are quite often used, specially in Generalised Exponentially Weighted Regression (GEWR) type models, introduced by Harrison and Akram (1982) and Akram (1984). This form is convenient, but usually not attractive for operation since the meaning of the parameters is not clear. To overcome this problem one needs a system of dynamic linear models in diagonal or any other meaningful form similar to canonical form. This is obtained by reparameterisation of a model to a desired form by similarity transformation of one system to another system through a transformation matrix. A general analytical expression for the elements of this matrix and its inverse, specially in case of canonical to diagonal transformation, is not known. One needs to compute these elements each time a transformation is sought. To ease this cumbersome problem a general recursive form of transformation matrix along with its inverse is presented for canonical to diagonal transformation. This general result apart from simplifying the process of transformation of linear dynamic systems helps us to reparameterise the models to a desired form.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
