3 citations · 3 across the 1 of their papers we have counts for
3 papers
stat.ME2020
Scalable changepoint and anomaly detection in cross-correlated data with an application to condition monitoring
Martin Tveten, Idris A. Eckley, Paul Fearnhead
Motivated by a condition monitoring application arising from subsea engineering we derive a novel, scalable approach to detecting anomalous mean structure in a subset of correlated…
stat.ME2019
Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored Projections
Martin Tveten, Ingrid K. Glad
When applying principal component analysis (PCA) for dimension reduction, the most varying projections are usually used in order to retain most of the information. For the purpose…
math.ST2019★ 3 cited
Which principal components are most sensitive to distributional changes?
Martin Tveten
PCA is often used in anomaly detection and statistical process control tasks. For bivariate data, we prove that the minor projection (the least varying projection) of the PCA-rotat…