Subjective Likelihood For An Assessment of Climate Change in the Ocean
by
Michael Lavine
University of Massachusetts

This talk describes a Bayesian statistical analysis of long term changes in the depth of the ocean's mixed layer. The data are thermal profiles recorded by ships. For this data there is no good sampling model and therefore no obvious likelihood function. Our approach is to elicit posterior distributions for training data directly from the expert. We then infer the likelihood function and use it on large data sets.

Date received: March 14, 2008