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Robustness of one-sided cross-validation to autocorrelation. (English) Zbl 1065.62068
Summary: The effects of moderate levels of serial correlation on one-sided and ordinary cross-validation in the context of local linear and kernel smoothing is investigated. It is shown both theoretically and by simulation that one-sided cross-validation is much less adversely affected by correlations than is ordinary cross-validation. The former method is a reliable means of window width selection in the presence of moderate levels of serial correlation, while the latter is not. It is also shown that ordinary cross-validation is less robust to correlation when applied to Gasser-Müller kernel estimators [T. Gasser and H.-G. Müller, Lect. Notes Math. 757, 23–68 (1979; Zbl 0418.62033)] than to local linear ones.
62G08Nonparametric regression
62M10Time series, auto-correlation, regression, etc. (statistics)
62G35Nonparametric robustness
65C60Computational problems in statistics