Limit distributions for linear programming time series estimators

The authors consider stationary autoregressive processes of order p which have positive innovations. They propose consistent parameter estimators based on linear programming. Under conditions, including regular variation of either the left or right tail of the innovations distribution, the authors prove that the estimators have a limit distribution. The rate of convergence of the present estimator is favorable compared with the Yule-Walker estimator under comparable circumstances.