Eliciting continuous probability distributions

Haggerty, Ryan P.

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https://hdl.handle.net/2142/24099 Copy

Description

Title

Eliciting continuous probability distributions

Author(s)

Haggerty, Ryan P.

Issue Date

2011-05-25T15:07:14Z

Director of Research (if dissertation) or Advisor (if thesis)

Abbas, Ali E.

Department of Study

Industrial&Enterprise Sys Eng

Discipline

Systems & Entrepreneurial Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Date of Ingest

2011-05-25T15:07:14Z

Keyword(s)

• Decision Analysis
• Probability Assessment
• Cumulative Prospect Theory

Abstract

The process of eliciting a representative probability distribution from a judge is fundamental to decision making under uncertainty. This work summarizes several aspects of eliciting continuous probability distributions. Through experimentation involving 103 judges the method of assessing single variable distributions by fixed variable or fixed probability method is compared. Slight, but consistent, superiority is shown by the fixed variable method. The use of iso-probability contours, a novel methodology for assessing joint probability distributions, is tested through experimentation. The ability of this method to assess a judges belief about the correlation of two variables is characterized. Further recommendations for the use of iso-probability contours are provided. The variable weighting function is introduced. This novel tool is designed to represent a subjects true belief about a continuous probability distribution as explained by cumulative prospect theory. Operating similarly to the probability weighting function, the variable weighting function allows an assessor to gain a judges belief about a specific variable value without requiring multiple assessments. Functional form of the variable weighting function is explored and relevant parameter values are provided.

Graduation Semester

2011-05

Permalink

http://hdl.handle.net/2142/24099

Copyright and License Information

Copyright 2011 Ryan Haggerty

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