Time series state-space approach

This work required a large amount of subsidiary R D in (1) hydrodynamic sediment-plant mesocosm design, replication, and monitoring, (2) synthetic and analytical chemistry, including the synthesis of commercially unavailable standards and development analytical approaches to detect minor differences in organic chemicals between time points and treatments and (3) sensor design, time series data acquisition and wavelet analysis of non-stationary series [6], and covariance structure modeling of mesocosm and ecosystem data [1]. Basic questions (e.g., what constitutes a true spatiotemporal replicate in a multivariate, multiply colinear system What is the minimum number of indicator variables needed to characterize the states of such a system and how often do they need to be sampled in space and time ) arose and had to... 

Given the pre-eminence of the transfer function and frequency-domain-based approaches in process and chemical engineering, these two approaches will be discussed in greatest detail in this chapter. Nevertheless, information about the state-space-based approach will also be considered. This chapter will present the basic, univariate approach to time series analysis, which will be extended in Chap. 6 to consider the multivariate case containing both stochastic and deterministic components in order to model complex processes for process control, economic analysis, and simulation development. 

The structural time series analysis methods also referred to as state-space methods [HAR 86, COM 07] have been used more and more for modeling the aggregate number of fatalities at national level [DUP 07], The approach that the authors adopt is innovative, as usually such analyses are led on an annual basis - in order to explain and forecast long-term changes in the aggregate number of fatalities at national level [LAS 01]). On the contrary, short-term changes can only be modeled on an infra-annual basis similar but uncompleted approaches were taken on a quarterly basis - without the inclusion of exogenous variables [COM 2007] and on a monthly basis - without the inclusion of economic variables [BER 13]. 

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