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Document Type:Latin Dissertation
Language of Document:English
Record Number:54681
Doc. No:TL24635
Call number:‭3391390‬
Main Entry:Calvin Homayoon Shirazi
Title & Author:Data-informed calibration and aggregation of expert opinion in a Bayesian frameworkCalvin Homayoon Shirazi
College:University of Maryland, College Park
Date:2009
Degree:Ph.D.
student score:2009
Page No:107
Abstract:Historically, decision-makers have used expert opinion to supplement lack of data. Expert opinion, however, is applied with much caution. This is because judgment is subjective and contains estimation error with some degree of uncertainty. The purpose of this study is to quantify the uncertainty surrounding the unknown of interest, given an expert opinion, in order to reduce the error of the estimate. This task is carried out by data-informed calibration and aggregation of expert opinion in a Bayesian framework. Additionally, this study evaluates the impact of the number of experts on the accuracy of aggregated estimate. The objective is to determine the correlation between the number of experts and the accuracy of the combined estimate in order to recommend an expert panel size.
Subject:Applied sciences; Aggregation; Bayesian; Calibration; Dependence; Expert; Judgment; Mechanical engineering; 0548:Mechanical engineering
Added Entry:A. Mosleh
Added Entry:University of Maryland, College Park