A robust method for shift detection in time series

H Dehling, R Fried and M Wendler

Biometrika, 2020, vol. 107, issue 3, 647-660

Abstract: SummaryWe present a robust and nonparametric test for the presence of a changepoint in a time series, based on the two-sample Hodges–Lehmann estimator. We develop new limit theory for a class of statistics based on two-sample U-quantile processes in the case of short-range dependent observations. Using this theory, we derive the asymptotic distribution of our test statistic under the null hypothesis of a constant level. The proposed test shows better overall performance under normal, heavy-tailed and skewed distributions than several other modifications of the popular cumulative sums test based on U-statistics, one-sample U-quantiles or M-estimation. The new theory does not involve moment conditions, so any transform of the observed process can be used to test the stability of higher-order characteristics such as variability, skewness and kurtosis.

Keywords: Changepoint test; Functional central limit theorem; Hodges–Lehmann estimator; Two-sample U-process; Two-sample U-quantile; Two-sample U-statistic; Weak dependence (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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