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Sequential Change Detection Under A Markov Setup With Unknown Pre-Change and Post-Change Distributions
Published: October 30, 2025 |
arXiv ID: 2510.26204v2
By: Ashish Bhoopesh Gulaguli, Shashwat Singh, Rakesh Kumar Bansal
Potential Business Impact:
Finds hidden changes in data faster.
Business Areas:
A/B Testing
Data and Analytics
In this work we extend the results developed in 2022 for a sequential change detection algorithm making use of Page's CUSUM statistic, the empirical distribution as an estimate of the pre-change distribution, and a universal code as a tool for estimating the post-change distribution, from the i.i.d. case to the Markov setup.
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Page Count
6 pages
Category
Mathematics:
Statistics Theory