Aggregating point estimates. A flexible modeling approach

Published

Journal Article

In many decision situations information is available from a number of different sources. Aggregating the diverse bits of information is an important aspect of the decision-making process but entails special statistical modeling problems in characterizing the information. Prior research in this area has relied primarily on the use of historical data as a basis for modeling the information sources. We develop a Bayesian framework that a decision maker can use to encode subjective knowledge about the information sources in order to aggregate point estimates of an unknown quantity of interest. This framework features a highly flexible environment for modeling the probabilistic nature and interrelationships of the information sources and requires straightforward and intuitive subjective judgments using proven decision-analysis assessment techniques. Analysis of the constructed model produces a posterior distribution for the quantity of interest. An example based on health risks due to ozone exposure demonstrates the technique.

Duke Authors

Cited Authors

  • Clemen, RT; Winkler, RL

Published Date

  • April 1, 1993

Published In

Volume / Issue

  • 39 / 4

Start / End Page

  • 501 - 516

International Standard Serial Number (ISSN)

  • 0025-1909

Citation Source

  • Scopus