Abstract
Functional Series Time-dependent AutoRegressive Moving Average (FS-TARMA) models constitute an important class of models for non-stationary signal modeling. However, the asymptotic properties of “general” (that is not necessarily periodically evolving) FS-TARMA estimators are not, yet, well understood. In the present study, a general framework for the asymptotic analysis of “general” FS-TARMA estimators is developed and applied to the case of “general” Weighted Least Squares, Maximum Likelihood and Multi Stage estimators. The validity of the asymptotic analysis results is confirmed through Monte Carlo experiments.
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