Optimal ensemble size for Ensemble-SCAN

Determine the optimal number of base SCAN detectors in the Ensemble-SCAN procedure, balancing stability across window sizes against the additional computational cost of including more detectors.

Background

Ensemble-SCAN aggregates detections from a finite collection of SCAN detectors using different window sizes. The supplementary material explains that increasing the ensemble size can improve stability across window choices but also increases computational cost, while the theoretical consistency argument treats the ensemble size as fixed.

The paper does not identify a theoretically or empirically optimal ensemble size. Resolving this question would clarify how the number of detectors should scale with the time-series length, available computational resources, and desired detection stability.

References

Although the literature does not provide an explicit optimal choice for the number of SCAN detectors in the ensemble, increasing this number excessively is not necessarily beneficial because it increases computational cost.

— SCAN: Sequentially Detecting Change-points via Adaptive Nonparametric Inference  (2608.28110 - Prabashwara et al., 28 Aug 2026) in Section “Computational Complexity and Parallel Implementation”