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 Lp 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 Lp-norm estimators on various stochastic processes.