On the maximum of covariance estimators

Moritz Jirak

Journal of Multivariate Analysis, 2011, vol. 102, issue 6, 1032-1046

Abstract: Let be a stationary process with mean 0 and finite variances, let [phi]h=E(XkXk+h) be the covariance function and its usual estimator. Under mild weak dependence conditions, the distribution of the vector is known to be asymptotically Gaussian for any , a result having important statistical consequences. Statistical inference requires also determining the asymptotic distribution of the vector for suitable d=dn-->[infinity], but very few results exist in this case. Recently, Wu (2009) [19] obtained tail estimates for the vector for some sequences dn-->[infinity] and used these to construct simultaneous confidence bands for , 1

Keywords: Asymptotic; extreme; value; distribution; Linear; process; Covariance; Short; memory (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (7)

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