Variance of the Sample Mean: Properties and Graphs of Quadratic-Form Estimators

Abstract

Many commonly used estimators of the variance of the sample mean from a covariance-stationary process can be written as quadratic forms. We study the class of quadratic-form estimators algebraically and graphically, including five specific types of estimators, some from the literature and some that are new. Finite and asymptotic bias, variance, and covariance are derived and examined, with emphasis on developing intuition and insight by interpreting these properties graphically. The graphs depict the nonoptimal statistical behavior of some of the simulation literature estimators such as nonoverlapping batch means, as well as the better behavior of estimators obtained by overlapping batches.