Value of information and the accuracy of discrete approximations

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dc.contributor.advisor Bickel , J . Eric
dc.contributor.committeeMember Lake , Larry W .
dc.creator Ramakrishnan , Arjun
dc.date.accessioned 2011 -01 -03T17 :53 :50Z
dc.date.accessioned 2011 -01 -03T17 :53 :57Z
dc.date.accessioned 2014 -02 -19T22 :48 :27Z
dc.date.available 2011 -01 -03T17 :53 :50Z
dc.date.available 2011 -01 -03T17 :53 :57Z
dc.date.available 2014 -02 -19T22 :48 :27Z
dc.date.created 2010 -08
dc.date.issued 2011 -01 -03
dc.date.submitted August 2010
dc.identifier.uri http : / /hdl .handle .net /2152 /ETD -UT -2010 -08 -1735
dc.description.abstract Value of information is one of the key features of decision analysis . This work deals with providing a consistent and functional methodology to determine VOI on proposed well tests in the presence of uncertainties . This method strives to show that VOI analysis with the help of discretized versions of continuous probability distributions with conventional decision trees can be very accurate if the optimal method of discrete approximation is chosen rather than opting for methods such as Monte Carlo simulation to determine the VOI . This need not necessarily mean loss of accuracy at the cost of simplifying probability calculations . Both the prior and posterior probability distributions are assumed to be continuous and are discretized to find the VOI . This results in two steps of discretizations in the decision tree . Another interesting feature is that there lies a level of decision making between the two discrete approximations in the decision tree . This sets it apart from conventional discretized models since the accuracy in this case does not follow the rules and conventions that normal discrete models follow because of the decision between the two discrete approximations . The initial part of the work deals with varying the number of points chosen in the discrete model to test their accuracy against different correlation coefficients between the information and the actual values . The latter part deals more with comparing different methods of existing discretization methods and establishing conditions under which each is optimal . The problem is comprehensively dealt with in the cases of both a risk neutral and a risk averse decision maker .
dc.format.mimetype application /pdf
dc.language.iso eng
dc.subject Discretization
dc.subject Value of information
dc.subject Discrete approximation
dc.subject Decision analysis
dc.subject Bayesian inference
dc.title Value of information and the accuracy of discrete approximations
dc.description.department Mechanical Engineering
dc.type.genre thesis *
dc.type.material text *
thesis.degree.name Master of Science in Engineering
thesis.degree.level Masters
thesis.degree.discipline Operations Research and Industrial Engineering
thesis.degree.grantor University of Texas at Austin
thesis.degree.department Mechanical Engineering
dc.date.updated 2011 -01 -03T17 :53 :57Z

Citation

Value of information and the accuracy of discrete approximations. Master's thesis, University of Texas at Austin. Available electronically from http : / /hdl .handle .net /2152 /ETD -UT -2010 -08 -1735 .

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