A bias-corrected, selfnormalized statistic based on a log-sum-exp smoothing of the supremum norm yields an asymptotically pivotal test for relevant changes in functional time series.
A note on estimating the change-point of a gradually changing stochastic process
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Selfnormalization for relevant inference with supremum-type statistics
A bias-corrected, selfnormalized statistic based on a log-sum-exp smoothing of the supremum norm yields an asymptotically pivotal test for relevant changes in functional time series.