A framework connects separable-covariance functional data to matrix-variate MMCD estimation and linear-complexity Shapley decompositions to deliver robust and explainable outlier detection.
Corollary B.0.1.Let X(t) =a ′ ϕ(t) be a rank m∈N stochastic process with mean µ and covariance κ, with coefficientsa∈R m and basisϕ= (ϕ 1,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Explainable Outlier Detection for Multivariate Functional Data
A framework connects separable-covariance functional data to matrix-variate MMCD estimation and linear-complexity Shapley decompositions to deliver robust and explainable outlier detection.