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Asymptotic expansion of the empirical process of long memory moving averages. (English) Zbl 1021.62072

Dehling, Herold (ed.) et al., Empirical process techniques for dependent data. Boston, MA: Birkhäuser. 213-239 (2002).
Summary: Moving averages in i.i.d. variables form one of the most important classes of long memory time series. The paper reviews various results on the asymptotic distribution of empirical processes of long memory moving averages with finite and infinite variance. It also discusses some interesting applications to goodness-of-fit testing for the marginal stationary error distribution in linear regression models and \(M\)-estimation in the one sample location model.
For the entire collection see [Zbl 1005.00016].

MSC:

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62E20 Asymptotic distribution theory in statistics
62G30 Order statistics; empirical distribution functions
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