Simon Wilson & R. Vatsa, The variational Bayes method for inverse regression problems with an application to the palaeoclimate reconstruction, Journal of Combinatorics, Information and System Sciences., 35, 1-2, 2010, 221 - 248
Journal of Combinatorics, Information and System Sciences. 35 1-2
The palaeoclimate reconstruction problem is described as an example of inverse regression
problems. In the reconstruction problem, past climate is inferred using pollen data. Modern
data is used to build a regression model of how pollen responds to climate. The inverse problem
is to infer climate from data on ancient pollen prevalence. The inverse inference presents a
challenging and computationally intensive problem. It is demonstrated that Variational Bayes
(VB), that assumes conditional independence, provides quick solutions to the reconstruction
problem. The advantage of the use of the VB method is that many more climate variables can
be included in the estimation without imposing a huge burden to the reconstruction problem.
We explore the accuracy of the VB method, and comment on its usefulness more generally in
inverse inference problems.
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