scholarly journals Exposure Models for the Prior Distribution in Bayesian Decision Analysis for Occupational Hygiene Decision Making

2013 ◽  
Vol 10 (2) ◽  
pp. 97-108 ◽  
Author(s):  
Eun Gyung Lee ◽  
Seung Won Kim ◽  
Charles E. Feigley ◽  
Martin Harper
2016 ◽  
Vol 5 (3) ◽  
pp. 80 ◽  
Author(s):  
Rose D. Baker ◽  
Ian G. McHale

The concept of shrinking bet size in Kelly betting to minimize estimated frequentist risk has recently been mooted. This rescaling appears to conflict with Bayesian decision theory through the likelihood principle and the complete class theorem; the Bayesian solution should already be optimal. We show theoretically and through examples that when the modeldetermining the likelihood function is correct, the prior distribution (if not dominated by data) is `correct' in a frequentist sense, and the posterior distribution is proper, then no further rescaling is required. However, if the model or the prior distribution is incorrect, or the posterior distribution improper, frequentist risk minimization can be a useful technique. We discuss how it might best be exploited. Another example, from maintenance, is used to show the wider applicability of the methodology; these conclusionsapply generally to decision-making.


2002 ◽  
Vol 45 (3) ◽  
pp. 175-184
Author(s):  
H. Korving ◽  
F. Clemens

In recent years, decision analysis has become an important technique in many disciplines. It provides a methodology for rational decision-making allowing for uncertainties in the outcome of several possible actions to be undertaken. An example in urban drainage is the situation in which an engineer has to decide upon a major reconstruction of a system in order to prevent pollution of receiving waters due to CSOs. This paper describes the possibilities of Bayesian decision-making in urban drainage. In particular, the utility of monitoring prior to deciding on the reconstruction of a sewer system to reduce CSO emissions is studied. Our concern is with deciding whether a price should be paid for new information and which source of information is the best choice given the expected uncertainties in the outcome. The influence of specific uncertainties (sewer system data and model parameters) on the probability of CSO volumes is shown to be significant. Using Bayes' rule, to combine prior impressions with new observations, reduces the risks linked with the planning of sewer system reconstructions.


Author(s):  
Michael Havbro Faber ◽  
Marc A. Maes

The present paper reviews and outlines the interpretation of uncertainties with a view to the various different categorizations introduced in the literature. A framework is then presented for risk based decision making taking basis in the Bayesian decision theory and recent methodical developments in risk assessment. It is emphasized that in principle all types of uncertainties should be included in formal decision analysis and that not doing so corresponds to informal decision analysis the quality of which may be difficult to judge. The controversial problem in engineering decision making of how to take into account uncertainties associated with the definition of the system being analyzed is outlined. For the typical situation where a discrete set of possible system representations is possible it is shown how a decision problem may be formulated for the identification of the optimal system to be considered as basis for decision making. The presented decision framework takes into account all prevailing uncertainties, epistemic as well as aleatory. Examples related to structural design and assessment problems relevant for offshore engineering are given illustrating how not to account for all types of uncertainties leads to sub-optimal decision making.


2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.


2009 ◽  
Vol 20 (9) ◽  
pp. 2574-2586 ◽  
Author(s):  
Yu-Xing SUN ◽  
Song-Hua HUANG ◽  
Li-Jun CHEN ◽  
Li XIE

2005 ◽  
Vol 165 (3) ◽  
pp. 403
Author(s):  
Uehara ◽  
Yokomizo ◽  
Iwasa

Author(s):  
Michael de Oliveira ◽  
Luis Soares Barbosa

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 124
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Florentin Smarandache ◽  
...  

Some decision-making problems, i.e., multi-criteria decision analysis (MCDA) problems, require taking into account the attitudes of a large number of decision-makers and/or respondents. Therefore, an approach to the transformation of crisp ratings, collected from respondents, in grey interval numbers form based on the median of collected scores, i.e., ratings, is considered in this article. In this way, the simplicity of collecting respondents’ attitudes using crisp values, i.e., by applying some form of Likert scale, is combined with the advantages that can be achieved by using grey interval numbers. In this way, a grey extension of MCDA methods is obtained. The application of the proposed approach was considered in the example of evaluating the websites of tourism organizations by using several MCDA methods. Additionally, an analysis of the application of the proposed approach in the case of a large number of respondents, done in Python, is presented. The advantages of the proposed method, as well as its possible limitations, are summarized.


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