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

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Rappold, AG; Lavine, M; Lozier, S

Published Date

  • September 1, 2007

Published In

Volume / Issue

  • 102 / 479

Start / End Page

  • 771 - 780

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1198/016214507000000761

Citation Source

  • Scopus