Abstract
AbstractStatistics based on the sample autocovariances are widely used in time‐series analysis. Estimators of the asymptotic covariance between the sample autocovariances are commonly derived from the so‐called Bartlett's formula. However, this formula essentially holds for linear processes. This entails that for a wide range of nonlinear time series the above‐mentioned estimators are not suitable. In this paper the behaviour of an alternative estimator is studied within the framework of centered or uncentered multivariate strongly mixing processes. Applications to differential functions of sample autocovariances, such as the sample autocorrelations, are considered.
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