Principal component analysis for river network data: use of spatiotemporal correlation and heterogeneous covariance structure

DOI10.1002/ENV.2753zbMATH Open1545.62824MaRDI QIDQ6626589

Hee-Seok Oh, Min-Su Park, Kyusoon Kim

Publication date: 28 October 2024

Published in: Environmetrics (Search for Journal in Brave)

zbMATH Keywords

CPCPCAspatial heterogeneitywater quality monitoringGWPCAflow-connected networkflow-directed PCA

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Cites Work

• Stepwise estimation of common principal components
• The approximation of one matrix by another of lower rank.
• Two generalizations of the common principal component model
• An Algorithm for Simultaneous Orthogonal Transformation of Several Positive Definite Symmetric Matrices to Nearly Diagonal Form
• A Generalized Least-Square Matrix Decomposition
• A Robust Regression Model for a First-Order Autoregressive Time Series with Unequal Spacing: Application to Water Monitoring
• Flow-directed PCA for monitoring networks
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