State-space models (SSM) are central to describe time-varying complex systems in countless signal processing applications such as remote sensing, networks, biomedicine, and finance name a few. Inference prediction SSMs possible when the model parameters known, which is rarely case. The estimation of these crucial, not only for performing statistical analysis, but also uncovering underlying stru...

In this paper, we consider function-indexed normalized weighted integrated periodograms for equidistantly sampled multivariate continuous-time state space models which are ARMA processes. Thereby, the sampling distance is fixed and driving Lévy process has at least a finite fourth moment. Under different assumptions on function moments of derive central limit theorem periodogram. Either assumpt...