Section: New Results
Dependent time changed processes
Participant : Valérie Monbet.
This is a collaboration with Pierre Ailliot (université de Bretagne Occidentale), Bernard Delyon (université de Rennes 1) and Marc Prevosto (IFREMER, Brest).
Many records in environmental sciences exhibit asymmetric trajectories and there is a need for simple and tractable models which can reproduce such feature. In  we explore an approach based on applying both a time change and a marginal transformation on Gaussian processes. The main originality of the proposed model is that the time change depends on the observed trajectory. We first show that the proposed model is stationary and ergodic and provide an explicit characterization of the stationary distribution. This result is then used to build both parametric and non–parametric estimate of the time change function whereas the estimation of the marginal transformation is based on up–crossings. Simulation results are provided to assess the quality of the estimates. The model is applied to wave data and it is shown that the fitted model is able to reproduce important statistics of the data such as its spectrum and marginal distribution which are important quantities for practical applications. An important benefit of the proposed model is its ability to reproduce the observed asymmetries between the crest and the troughs and between the front and the back of the waves by accelerating the chronometer in the crests and in the front of the waves.