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Comparison of linear interpolation and arctan approximation of one-dimensional monotonic utility functions based on experimental data

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Języki publikacji
EN
Abstrakty
EN
Elicitation of utilities is among the most time consuming tasks in decision analysis. We search for ways to shorten this phase without compromising the quality of results. We use the results from an empirical experiment with 104 participants. They elicited 9 inner nodes from their one-dimensional utility function over monetary gains and losses using three elicitation techniques. A specific feature of the results is their interval character, as the elicitators are fuzzy rational individuals. The data is used to construct arctan-approximated and linearly interpolated utilities and to compare the results. We form partial samples with 3, 4 and 5 nodes for each participant and each elicitation method, and again interpolate/approximate the utilities. We introduce goodness-of-fit and deterioration measures to analyze the decrease in quality of the utility function due to reduced data nodes. The analysis, using paired-sample tests, leads to the following conclusions: 1) arctan-approximation is more adequate than linear interpolation over the whole samples; 2) 5 inner nodes are sufficient to construct a satisfactory arctan-approximation; 3) arctan-approximation and linear interpolation are almost equal in quality over the partial samples, but the local risk aversion of the linearly interpolated utility function is of poor quality unlike that of the arctan-approximated utility function.
Rocznik
Strony
835--861
Opis fizyczny
Bibliogr. 19 poz., wykr.
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autor
autor
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Bibliografia
  • CLEMEN, R. (1996) Making Hard Decisions: an Introduction to Decision Analysis. Second Edition. Duxbury Press, Wadsworth Publishing Company.
  • EFRON, B. and TIBSHIRANI, R.J. (1993) An Introduction to the Bootstrap. Chapman & Hall.
  • FARQUHAR, P.H. (1984) Utility Assessment Methods. Management Science 30 (11), 1283-1300.
  • FRENCH, S. (1993) Decision Theory: an Introduction to the Mathematics of Rationality. Ellis Horwood.
  • FRENCH, S. and INSUA, D.R. (2000) Statistical Decision Theory. Arnold.
  • KEENEY, R.L. and RAIFFA, H. (1993) Decisions with Multiple Objectives: Preference and Value Tradeoffs. Cambridge University Press.
  • MCCORD, M. and DE NEUFVILLE, R. (1986) Lottery Equivalents: Reduction of the Certainty Effect Problem in Utility Assessment. Management Science 32, 56-60.
  • NIKOLOVA, N.D. (2007) Elicitation Errors in One-Dimensional Non-Monotonic Utility Functions. Computer Science and Technology 2, 48-59.
  • NIKOLOVA, N.D., SHULUS, A., TONEVA, D. and TENEKEDJIEV, K. (2005) Fuzzy Rationality in Quantitative Decision Analysis. Journal of Advanced Computational Intelligence and Intelligent Informatics 9 (1), 65-69.
  • PRATT, J.W. (1964) Risk aversion in the small and in the large. Econometrica 32, 122-136.
  • PRESS, W.H., TEUKOLSKY, S.A., VETTERLING, W.T. and FLANNERY, B.P. (1992) Numerical Recipes - the Art of Scientific Computing. Cambridge University Press.
  • TENEKEDJIEV, K., NIKOLOVA, N.D. and DIMITRAKIEV, D. (2004) Application of the Triple Bisection Method for Extraction of Subjective Utility Information. Proc. Second International Conference “Management and Engineering ‘2004”, 2 (7), 115-117, Sofia, Bulgaria.
  • TENEKEDJIEV, K., NIKOLOVA, N.D. and DIMITRAKIEV, D. (2008) Analytical One-Dimensional Utility - Comparison of Power and Arctg-Approximation. Engineering Sciences 4, 20-34 (in Bulgarian).
  • TENEKEDJIEV, K., NIKOLOVA, N.D. and PFLIEGL, R. (2006) Utility Elicitation with the Uncertain Equivalence Method. Comptes rendus de I’academie Bulgare des sciences 59 (3), 283-288.
  • THE MATHWORKS (2006) MATLAB Statistical Toolbox 3 - User’s Guide. The Math Works Inc.
  • TRAUTMANN, H. and WEIHS, C. (2006) On the Distribution of the Desirability Index using Harrington’s Desirability Function. Metrika 63 (2), 207-213.
  • TVERSKY, A. and KAHNEMAN, D. (1974) Judgment under Uncertainty: Heuristics and Biases. Science 185, 1124-1131.
  • VON NEUMANN, J. and MORGENSTERN, O. (1947) Theory of Games and Economic Behaviour, Second Edition. Princeton University Press.
  • WAKKER, P. and DENEFFE, D. (1996) Eliciting Von Neumann-Morgenstern Utilities when Probabilities are Distorted or Unknown. Management Science 42, 1131-1150.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0041-0021
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