Smooth estimation of error distribution in nonparametric regression under long memory. (English) Zbl 1366.62083
Antoch, Jaromír (ed.) et al., Analytical methods in statistics, AMISTAT. Proceedings of the workshop, Prague, Czech Republic, November 10–13, 2015. Cham: Springer (ISBN 978-3-319-51312-6/hbk; 978-3-319-51313-3/ebook). Springer Proceedings in Mathematics & Statistics 193, 73-104 (2017).
Summary: We consider the problem of estimating the error distribution function in a nonparametric regression model with long memory design and long memory errors. This paper establishes a uniform reduction principle of a smooth weighted residual empirical distribution function estimator. We also investigate consistency property of local Whittle estimator of the long memory parameter based on nonparametric residuals. The results obtained are useful in providing goodness of fit test for the marginal error distribution and in prediction under long memory.
For the entire collection see [Zbl 1367.62010].
For the entire collection see [Zbl 1367.62010].
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