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Monte Carlo methods for Bayesian palaeoclimate reconstruction

Summary: Monte Carlo methods for Bayesian
palaeoclimate reconstruction
Jonathan Rougier
Department of Mathematics
University of Bristol
Source: supranetAddendum.tex, March 28, 2011
In palaeoclimate reconstruction, the natural modelling direction is for-
wards from climate to sensors to proxy measurements. Statistical methods
can be used to invert this direction, making climate inferences from proxy
measurements. Among these methods, the Bayesian method would seem to
deal best with the substantial epistemic uncertainties about climate, and
about its impact on sensors. The main challenge is to perform this inference
efficiently within a simulation approach. This paper reviews the Importance
Sampling approach to Bayesian palaeoclimate reconstruction, and then goes
on to demonstrate the value of recent advances in Markov chain Monte Carlo
(MCMC) inference.
Keywords: MCMC, pseudo-marginal
1 Brief introduction
One purpose of this note is to provide precision and justification for the simulation-


Source: Applebaum, David - Department of Probability and Statistics, University of Sheffield


Collections: Mathematics