Physically motivated scale interaction parameterization in reduced rank quadratic nonlinear dynamic spatio‐temporal models

DOI10.1002/env.2266zbMath1525.62125OpenAlexW1516400850MaRDI QIDQ6090030

Daniel W. Gladish, Christopher K. Wikle

Publication date: 15 December 2023

Published in: Environmetrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/env.2266

zbMATH Keywords

spatialBayesianhierarchicalempirical orthogonal functions

Mathematics Subject Classification ID

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

Related Items (1)

A Review of Data‐Driven Discovery for Dynamic Systems

Cites Work

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• Fundamental limitations of ad hoc linear and quadratic multi-level regression models for physical systems
• A general science-based framework for dynamical spatio-temporal models
• The Bayesian Lasso
• Spatiotemporal Hierarchical Bayesian Modeling Tropical Ocean Surface Winds
• Physics constrained nonlinear regression models for time series
• Polynomial nonlinear spatio‐temporal integro‐difference equation models

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