The classical statistical model relates to n independent random variables having a common distribution. In this paper we consider the situation where the common distribution involves an unknown parameter, and where at time 0<t<1 only the first [nt] random variables are observed.

We study the generalized assignment problem, under a probabilistic model for its cost and requirement parameters. First we address the issue of feasibility by deriving a tight condition on the probabilistic model that ensures that the corresponding problem instances are feasible with the...

In this paper we extend the univariate periodic integration model to multivariate cointegrated time series. We analyze representation issues of a multivariate periodic model. We argue that simple adding an index s to the parameters in an otherwise nonperiodic Vector AutoRegression (VAR) leads to...