3 citations · 5 across the 6 of their papers we have counts for
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stat.ME2019★ 2 cited
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…