Coherence Analysis of Multivariate Time Series
Seminar Room 1, Newton Institute
Data collection systems are widely used within the energy sector to record process activity across energy generations sites. These loggers are capable of sampling data at high rates, at a number of locations and recording multiple process aspects at each location. Such series are typically non-stationary in nature, with potentially time-varying dependence between the various series components. In this talk we consider the problem of modelling and estimating the coherence structure within such time series. In particular we focus on the challenge of identifying whether the dependence between a pair of components is direct or indirectly driven by other components of the series, illustrating our approach using an example from wind energy.