Standardized Time Series Lp-Norm Variance Estimators for Simulations

This paper studies a class of estimators for the variance parameter of a stationary stochastic process. The estimators are based on L_p norms of standardized time series, and they generalize previously studied estimators due to Schruben. We show that the new estimators have some desirable properties: they are asymptotically unbiased and have low asymptotic variance. We also illustrate empirically the performance of the L_p-norm estimators on various stochastic processes.