تقرير
Robust Score-Based Quickest Change Detection
| العنوان: | Robust Score-Based Quickest Change Detection |
|---|---|
| المؤلفون: | Moushegian, Sean, Wu, Suya, Diao, Enmao, Ding, Jie, Banerjee, Taposh, Tarokh, Vahid |
| سنة النشر: | 2024 |
| المجموعة: | Statistics |
| مصطلحات موضوعية: | Statistics - Methodology, Electrical Engineering and Systems Science - Signal Processing, Statistics - Machine Learning |
| الوصف: | Methods in the field of quickest change detection rapidly detect in real-time a change in the data-generating distribution of an online data stream. Existing methods have been able to detect this change point when the densities of the pre- and post-change distributions are known. Recent work has extended these results to the case where the pre- and post-change distributions are known only by their score functions. This work considers the case where the pre- and post-change score functions are known only to correspond to distributions in two disjoint sets. This work employs a pair of "least-favorable" distributions to robustify the existing score-based quickest change detection algorithm, the properties of which are studied. This paper calculates the least-favorable distributions for specific model classes and provides methods of estimating the least-favorable distributions for common constructions. Simulation results are provided demonstrating the performance of our robust change detection algorithm. Comment: arXiv admin note: text overlap with arXiv:2306.05091 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.11094 |
| رقم الأكسشن: | edsarx.2407.11094 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |