A Bayesian Interpretation of Data Trimming to Remove Excess Claims,

Abstract

The effect of excess or catastrophic claims is well recognized in insurance. For example, in experience rating it is customary to truncate the data to minimize the effect of such outliers; Gisler has recently proposed a credibility formula using such data trimming. This paper develops a model of the excess claims process and finds the exact Bayesian forecast. The resulting forecast form is approximately a data trim, thus justifying the simpler, heuristic approach.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1981
Accession Number
ADA111807

Entities

People

  • William S. Jewell

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Bayesian Networks
  • California
  • Consistency
  • Contamination
  • Insurance
  • Integrals
  • Lepidoptera
  • Models
  • Observation
  • Probability
  • Random Variables
  • Weighting Functions

Readers

  • Educational Psychology
  • Marine Hydrodynamics
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference