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Sequential Change Detection through Empirical Distribution and Universal Codes

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arxiv 2112.07549 v1 pith:TJCFBQWP submitted 2021-12-14 cs.IT math.IT

Vikrant Malik , R. K. Bansal This is my paper · ORCID
classification cs.ITmath.IT
keywords distributioncusummodifiedtestbeenchangedetectionempirical
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Universal compression algorithms have been studied in the past for sequential change detection, where they have been used to estimate the post-change distribution in the modified version of the Cumulative Sum (CUSUM) Test. In this paper, we introduce a modified CUSUM test where the pre-change distribution is also unknown and an empirical version of the pre-change distribution is used to implement the algorithm. We present a study of various characteristics of this modified CUSUM Test and then prove its asymptotic optimality.

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Cited by 1 Pith paper

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  1. Non-partitioned e-detectors for nonparametric sequential change detection

    stat.ME 2026-07 accept novelty 7.0 of 10

    Aggregating point-null e-processes and minimizing over candidate no-change laws yields ARL- and PFA-valid non-partitioned change detectors with first-order optimal delay under local REGROW conditions.

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