Evolving Bayesian Emulators for Structured Chaotic Time Series, with Application to Large Climate Models

DOI10.1137/120900915zbMath1349.62433OpenAlexW2067794591MaRDI QIDQ2938432

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Publication date: 14 January 2015

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/120900915

zbMATH Keywords

Bayesian analysistime seriesclimate modelsMarkov chain Monte Carlo algorithmuncertainty quantificationdynamic emulationGaussian processses

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Gaussian processes (60G15) Design of statistical experiments (62K99) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Bayesian problems; characterization of Bayes procedures (62C10) Meteorology and atmospheric physics (86A10)

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Posterior belief assessment: extracting meaningful subjective judgements from Bayesian analyses with complex statistical models ⋮ Efficient emulation of computer models utilising multiple known boundaries of differing dimension ⋮ Exploratory ensemble designs for environmental models using k‐extended Latin Hypercubes ⋮ A comparison of statistical emulation methodologies for multi‐wave calibration of environmental models ⋮ A Bayesian computer model analysis of robust Bayesian analyses ⋮ Emulating dynamic non-linear simulators using Gaussian processes ⋮ Compression and Conditional Emulation of Climate Model Output ⋮ Diagnostics-Driven Nonstationary Emulators Using Kernel Mixtures

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