The Credible Distribution.

Abstract

Credibility theory is concerned with the problem of forecasting the mean performance (claim frequency, total losses, etc.) of an individual risk, selected from a collective of heterogeneous risks, based upon the statistics of the collective, and upon the individual's experience data. The classic results, derived by American actuaries in the 1920's, were further strengthened by Bailey and Mayerson in 1950 and 1965, who showed that these results were exact Bayesian for certain risk distributions. Buhlmann, in 1967, then showed that the credibility formulae were the best least-squares linearized approximation to the exact Bayesian forecast, for general risk distributions. The paper extends credibility theory to the problem of forecasting the distribution of individual risk, based upon collective statistics and individual experience data. (Modified author abstract)

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1973
Accession Number
AD0767979

Entities

People

  • William S. Jewell

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Collaborative Techniques
  • Computing-Related Activities
  • Data Science
  • Delphi Method
  • Frequency
  • Information Science
  • Statistics

Readers

  • Aviation Safety Risk Assessment.
  • Statistical inference.
  • Strategic Security Studies

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - DoD AI Strategy