Exploiting the structure of autoregressive processes in chance-constrained multistage stochastic linear programs

We consider an interstage dependent stochastic process whose components follow an autoregressive model with time varying order. At a given time, we give some recursive formulæ linking future values of the process with past values and noises. We then consider multistage stochastic linear programs with uncertain sets depending affinely on such processes. At each stage, dealing with uncertainty using probabilistic constraints, the recursive relations can be used to obtain explicit expressions for the feasible set.