Standardized Time Series Lp-Norm Variance Estimators for Simulations
研究了一类基于标准化时间序列Lp范数的方差参数估计量，证明了其渐近无偏性和低渐近方差，并通过多种随机过程实证了其性能。
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.