Develops a bivariate partial sum process and self-normalized CUSUM test for detecting mean changes in locally stationary time series, with proven weak convergence and asymptotic level/consistency properties.
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Self-Normalization for CUSUM-based Change Detection in Locally Stationary Time Series
Develops a bivariate partial sum process and self-normalized CUSUM test for detecting mean changes in locally stationary time series, with proven weak convergence and asymptotic level/consistency properties.