Just as ARMA processes play a central role in the representation of stationary time series with discrete time parameter, Y_n, CARMA processes play an analogous role in the representation of stationary time series with continuous time parameter, Y(t). Levy-driven CARMA processes permit the modelling of heavy-tailed and asymmetric time series and incorporate both distributional and sample-path information. In this talk we review recent results in the theory and application of these processes, and an extension to a class of random fields on R^n.
How to participate in this seminar:
1. Book your nearest ACE facility;
2. Notify the seminar convenor at La Trobe University (Andriy Olenko) to notify you will be participating.
No access to an ACE facility? Contact Maaike Wienk to arrange a temporary Visimeet licence for remote access (limited number of licences available – first come first serve)