Ricerc@Sapienza

When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model.

Acoustic communications in underwater environment are considerably influenced by the physical characteristics of the medium. This is even more true in the polar regions where the presence of icebergs and icy water layers represent an additional dependence to the signal propagation. Considering a MIMO scenario, we investigate how the channels spatial correlation is conditioned in the case of both frozen and fluid water surface. More, we evaluate the impact of the medium changes on the signal delay spread.