Figure 1.

Time series and running correlation plots for the toy example. In (a), a time series comprised of three variables drawn from a multivariate normal distribution with zero means is displayed. In the baseline phases (white background), variables are uncorrelated and have a unit variance such that the covariance matrix is equal to $\left[\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right]$. In the middle phase (gray background), an event is introduced such that the correlation between the first two variables increase, giving a covariance matrix of $\left[\begin{array}{ccc}1& 0.7& 0\\ 0.7& 1& 0\\ 0& 0& 1\end{array}\right]$. In (b), the running correlations obtained using a window size of 25 time points are exhibited.