A Bayesian Interpretation of Data Trimming to Remove Excess Claims. Excess Claims and Data Trimming in the Context of Credibility Rating Procedures.

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 at data trim, thus justifying the simpler, heuristic approach. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1981
Accession Number
ADA111690

Entities

People

  • Alois Gisler
  • Hans Buehlmann
  • William S. Jewell

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Bayesian Networks
  • California
  • Distribution Functions
  • Estimators
  • Heuristic Methods
  • Insurance
  • Mathematics
  • Models
  • Normal Distribution
  • Operations Research
  • Probability
  • Random Variables
  • Standards
  • Truncation
  • United States
  • Universities

Readers

  • Economics
  • Regression Analysis.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference