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