5 papers · 1 filter
CHASM: Online Changepoint Detection in Temporal and Cross-Variable Dependence
Victor K. Khamesi, Edward A. K. Cohen, Niall M. Adams +1
Changepoint detection identifies times when the generative process of a time series changes, with applications in healthcare, cybersecurity, and finance. In multivariate settings,…
Scale two-sample testing with arbitrarily missing data
Yijin Zeng, Niall M. Adams, Dean A. Bodenham
This work proposes a novel rank-based scale two-sample testing method for univariate, distinct data when a subset of the data may be missing. Our approach is based on mathematicall…
Exact Bounds of Spearman's footrule in the Presence of Missing Data with Applications to Independence Testing
Yijin Zeng, Niall M. Adams, Dean A. Bodenham
This work studies exact bounds of Spearman's footrule between two partially observed -dimensional distinct real-valued vectors and . The lower bound is obtained by sequen…
Online Changepoint Detection via Dynamic Mode Decomposition
Victor K. Khamesi, Niall M. Adams, Dean A. Bodenham +1
Detecting changes in data streams is a vital task in many applications. There is increasing interest in changepoint detection in the online setting, to enable real-time monitoring…
MMD Two-sample Testing in the Presence of Arbitrarily Missing Data
Yijin Zeng, Niall M. Adams, Dean A. Bodenham
In many real-world applications, it is common that a proportion of the data may be missing or only partially observed. We develop a novel two-sample testing method based on the Max…