  Time lags are ubiquitous in biophysiological processes and more generally in
real-world complex networks. It has been recently proposed to use
information-theoretic tools such as transfer entropy to detect and estimate a
possible delay in the couplings. In this work, we focus on stationary linear
stochastic processes in continuous time and compute the transfer entropy in the
presence of delay and correlated noises, using an approximate but numerically
effective solution to the relevant Wiener-Hopf factorization problem. Our
results rectify and complete the recent study of [1].
