Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis

DOI10.1098/rspa.2018.0854zbMath1472.86001arXiv1803.08482OpenAlexW2793717814WikidataQ63930885 ScholiaQ63930885MaRDI QIDQ5160651

No author found.

Publication date: 29 October 2021

Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1803.08482

zbMATH Keywords

model selectionmodel calibrationstatisticsuncertainty quantificationclimate reconstructionclimatologypalaeoclimateglacial-interglacial cycle

Mathematics Subject Classification ID

General questions in geophysics (86A04)

Related Items (3)

Nonparametric Bayesian volatility estimation for gamma-driven stochastic differential equations ⋮ Bayesian model evaluation for multiple scenarios ⋮ Nonlinear climate dynamics: from deterministic behaviour to stochastic excitability and chaos

Cites Work

• Unnamed Item
• The pseudo-marginal approach for efficient Monte Carlo computations
• Flexible paleoclimate age-depth models using an autoregressive gamma process
• Sequential Monte Carlo Samplers
• Sequential Monte Carlo Methods for Dynamic Systems
• Particle Markov Chain Monte Carlo Methods
• Bayes Factors
• SMC2: An Efficient Algorithm for Sequential Analysis of State Space Models

This page was built for publication: Quantifying age and model uncertainties in palaeoclimate data and dynamical climate models with a joint inferential analysis