Subjective likelihood for the assessment of trends in the ocean's mixed-layer depth

This article 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 these data, there is no good sampling model and thus 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 dataseis. © 2007 American Statistical Association.

Duke Scholars

Author M. Susan Lozier Earth and Climate Sciences