Date of Award

1-1-1976

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.) in Systems Science

Department

Systems Science

Physical Description

v, 111 leaves: ill. 28 cm.

Subjects

Operations research, Expert Evidence, Bayesian statistical decision theory, Decision making

DOI

10.15760/etd.597

Abstract

Subjective information is a valuable resource; however, decisionmakers often ignore it because of difficulties in eliciting it from assessors. This thesis is on Bayesian inquiry and it presents an approach to eliciting subjective information from assessors. Based on the concepts of cascaded inference and Bayesian statistics, the approach is designed to reveal to the decision-maker the way in which the assessor considers his options and the reasons he has for selecting particular alternatives. Unlike previous works on cascaded inferences, the approach here focuses on incoherency. Specifically, it employs the use of additional information to revise and check the estimates. The reassessment may be done directly or indirectly. The indirect procedure uses a second order probability or type II distribution. An algorithm utilizing this approach is also presented. The methodology is applicable to any number of assessors. Procedures for aggregating and deriving surrogate distributions are also proposed.

Description

Portland State University. Systems Science Ph. D. Program.

Persistent Identifier

http://archives.pdx.edu/ds/psu/4486

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