Behavioural Approximation of Stochastic Processes by Rank Reduced Spectra
Behaviours provide an elegant, parameter free characterization of deterministic systems. We discuss a possible application of behaviours in the approximation of stochastic systems. This can be seen as an extension to the dynamic case of the well-known static factor analysis model. An essential difference is that we see modelling primarily as a matter of process approximation, not as a method to recover the true data generating process. In particular we see "noise properties" as a kind of prior model assumption that can be compared with the resulting quality of the process approximation.
|Keywords||behaviours, factor analysis, least squares, lineair systems, stationary processes|
Heij, C., & Scherrer, W.. (1996). Behavioural Approximation of Stochastic Processes by Rank Reduced Spectra (No. EI 9610/A). Retrieved from http://hdl.handle.net/1765/1374