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Reliability of Subjective Probability Forecasts of Precipitation and Temperature

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  • Allan H. Murphy
  • Robert L. Winkler

Abstract

This paper briefly describes some results of operational and experimental programmes in the United States involving subjective probability forecasts of precipitation occurrence and of maximum and minimum temperatures. These results indicate that weather forecasters can formulate such forecasts in a reliable manner.

Suggested Citation

  • Allan H. Murphy & Robert L. Winkler, 1977. "Reliability of Subjective Probability Forecasts of Precipitation and Temperature," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(1), pages 41-47, March.
    • Handle: RePEc:bla:jorssc:v:26:y:1977:i:1:p:41-47
    DOI: 10.2307/2346866
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    Cited by:

    1. Dharmasena, Senarath & Bessler, David & Capps, Oral. Jr, 2016. "On the Evaluation of Probability Forecasts: An Application to Qualitative Choice Models," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235424, Agricultural and Applied Economics Association.
    2. James S. Dyer & James E. Smith, 2021. "Innovations in the Science and Practice of Decision Analysis: The Role of Management Science," Management Science, INFORMS, vol. 67(9), pages 5364-5378, September.
    3. K J Wilson & M Farrow, 2010. "Bayes linear kinematics in the analysis of failure rates and failure time distributions," Journal of Risk and Reliability, , vol. 224(4), pages 309-321, December.
    4. Olszewski, Wojciech, 2015. "Calibration and Expert Testing," Handbook of Game Theory with Economic Applications,, Elsevier.
    5. James K. Hammitt & Alexander I. Shlyakhter, 1999. "The Expected Value of Information and the Probability of Surprise," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 135-152, February.
    6. Josef Frysak & Edward W. N. Bernroider & Konradin Maier, 2017. "An Effort Feedback Perspective on Persuasive Decision Aids for Multi-Attribute Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 161-181, January.
    7. Victor Richmond R. Jose & Robert L. Winkler, 2009. "Evaluating Quantile Assessments," Operations Research, INFORMS, vol. 57(5), pages 1287-1297, October.
    8. Jain, Kriti & Bearden, J. Neil & Filipowicz, Allan, 2013. "Depression and forecast accuracy: Evidence from the 2010 FIFA World Cup," International Journal of Forecasting, Elsevier, vol. 29(1), pages 69-79.
    9. David Bessler & Robert Ruffley, 2004. "Prequential analysis of stock market returns," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 399-412.
    10. M Revie & T Bedford & L Walls, 2010. "Evaluation of elicitation methods to quantify Bayes linear models," Journal of Risk and Reliability, , vol. 224(4), pages 322-332, December.
    11. repec:cup:judgdm:v:9:y:2014:i:5:p:445-464 is not listed on IDEAS
    12. Gudmundsson, Sveinn Vidar & Lechner, Christian, 2013. "Cognitive biases, organization, and entrepreneurial firm survival," European Management Journal, Elsevier, vol. 31(3), pages 278-294.
    13. D. Marc Kilgour & Yigal Gerchak, 2004. "Elicitation of Probabilities Using Competitive Scoring Rules," Decision Analysis, INFORMS, vol. 1(2), pages 108-113, June.
    14. Abel Sancarlos & Edgar Bahilo & Pablo Mozo & Lukas Norman & Obaid Ur Rehma & Mihails Anufrijevs, 2023. "Towards a data-driven debt collection strategy based on an advanced machine learning framework," Papers 2311.06292, arXiv.org.
    15. Saiwing Yeung, 2014. "Framing effect in evaluation of others' predictions," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 445-464, September.
    16. Miley W. Merkhofer & Ralph L. Keeney, 1987. "A Multiattribute Utility Analysis of Alternative Sites for the Disposal of Nuclear Waste," Risk Analysis, John Wiley & Sons, vol. 7(2), pages 173-194, June.
    17. Fergus Bolger & Gene Rowe, 2015. "The Aggregation of Expert Judgment: Do Good Things Come to Those Who Weight?," Risk Analysis, John Wiley & Sons, vol. 35(1), pages 5-11, January.
    18. Stephen C. Hora, 2010. "An Analytic Method for Evaluating the Performance of Aggregation Rules for Probability Densities," Operations Research, INFORMS, vol. 58(5), pages 1440-1449, October.
    19. Mary Kynn, 2008. "The ‘heuristics and biases’ bias in expert elicitation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 239-264, January.
    20. Dimitriadis, Timo & Gneiting, Tilmann & Jordan, Alexander I. & Vogel, Peter, 2024. "Evaluating probabilistic classifiers: The triptych," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1101-1122.
    21. Kriti Jain & Kanchan Mukherjee & J. Neil Bearden & Anil Gaba, 2013. "Unpacking the Future: A Nudge Toward Wider Subjective Confidence Intervals," Management Science, INFORMS, vol. 59(9), pages 1970-1987, September.
    22. Richard D. Johnson & George M. Marakas, 2000. "Research Report: The Role of Behavioral Modeling in Computer Skills Acquisition: Toward Refinement of the Model," Information Systems Research, INFORMS, vol. 11(4), pages 402-417, December.
    23. Astebro, Thomas B. & Fossen, Frank M. & Gutierrez, Cédric, 2024. "Entrepreneurs: Clueless, Biased, Poor Heuristics, or Bayesian Machines?," IZA Discussion Papers 17231, Institute of Labor Economics (IZA).
    24. Jeryl L. Mumpower & Steven Livingston & Thomas J. Lee, 1987. "Expert judgments of political riskiness," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 51-65.
    25. McKenzie, Craig R.M. & Liersch, Michael J. & Yaniv, Ilan, 2008. "Overconfidence in interval estimates: What does expertise buy you?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 107(2), pages 179-191, November.

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