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From the Editor ---Median Aggregation, Scoring Rules, Expert Forecasts, Choices with Binary Attributes, Portfolio with Dependent Projects, and Information Security

Author

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  • Rakesh K. Sarin

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095-1481)

Abstract
The December issue of Decision Analysis contains six articles. Our first three papers aim to improve the quality of probability judgments. Hora, Fransen, Hawkins, and Susel argue that medium aggregation of distribution functions works better than mean aggregation of probabilities. Merkle and Steyvers examine the relative attractiveness of different scorings rules. Karvetski, Olson, Mandel, and Twardy propose a coherence weighted probability aggregation rule for combining expert forecasts. Our fourth paper by Katsikopoulos presents a theory that explains why simple heuristics often perform well in multiattribute choices with binary attributes. Bhattacharjya, Eidsvik, and Mukerji provide closed-form results for value of information in the context of portfolio selection with dependent projects. Finally, Gao, Zhong, and Mei use game theory to analyze information security. All of the papers have a common purpose of improving decisions in private and public domains.

Suggested Citation

  • Rakesh K. Sarin, 2013. "From the Editor ---Median Aggregation, Scoring Rules, Expert Forecasts, Choices with Binary Attributes, Portfolio with Dependent Projects, and Information Security," Decision Analysis, INFORMS, vol. 10(4), pages 277-278, December.
    • Handle: RePEc:inm:ordeca:v:10:y:2013:i:4:p:277-278
    DOI: 10.1287/deca.2013.0284
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    References listed on IDEAS

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    1. Mark J. Schervish & Teddy Seidenfeld & Joseph B. Kadane, 2009. "Proper Scoring Rules, Dominated Forecasts, and Coherence," Decision Analysis, INFORMS, vol. 6(4), pages 202-221, December.
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