We consider the basic problem of refi tting a time series over a finite period of time and formulate it as a stochastic dynamic program. By changing the underlying Markov decision process we are able to obtain a model that at optimality considers historical data as well as forecasts of future...

This thesis consists of two parts. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis consists of two chapters. One chapter is concerned with the development of efficient estimators of the marginal distribution functions...