Modern statistical methods in oceanography: a hierarchical perspective

DOI10.1214/13-STS436zbMath1331.86031arXiv1312.5904MaRDI QIDQ5965037

Radu Herbei, Christopher K. Wikle, Ralph F. Milliff, William B. Leeds

Publication date: 2 March 2016

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1312.5904

zbMATH Keywords

ecosystemquadratic nonlinearityBayesianbiogeochemicalocean vector windssea surface temperaturespatio-temporalstate-space

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Hydrology, hydrography, oceanography (86A05) Research exposition (monographs, survey articles) pertaining to statistics (62-02) Geostatistics (86A32) Research exposition (monographs, survey articles) pertaining to geophysics (86-02)

Related Items (2)

A Monte Carlo approach to quantifying discrepancies between intractable posterior distributions ⋮ Learning excursion sets of vector-valued Gaussian random fields for autonomous ocean sampling

Uses Software

• EnKF
• spBayes
• BayesDA

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