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Calibrating and Combining Precipitation Probability Forecasts

  • Robert T. Clemen
  • Robert L. Winkler

Abstract

Imagine a decision maker who has heard from one or more information sources regarding the probability of some future event and who desires to use this information to revise his personal beliefs concerning the event. One approach to this problem involves the decision maker treating the probabilities as data in a Bayesian inferential problem, the output of which is an updated probability regarding the event in question. The thorniest part of the Bayesian combination procedure is the assessment of a likelihood function by the decision maker to represent his beliefs regarding the quality of the information and, in the case of multiple sources, the nature of the dependence among the sources.

Keywords

Mean Square Error Lead Time Cool Season National Weather Service Combine Forecast 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Agnew, C. E., 1985, Multiple probability assessments by dependent experts. J. Amer. Statist. Assoc. 80 ,343–347.MathSciNetMATHCrossRefGoogle Scholar
  2. Armstrong, J. S., 1984, Forecasting by extrapolation: conclusions from 25 years of research, Interfaces 14 (6) ,52–66.CrossRefGoogle Scholar
  3. Chang, K., 1985, “Combination of Opinions: The Expert Problem and the Group Consensus Problem,” Ph.D. Dissertation, University of California, Berkeley, CA.Google Scholar
  4. Clemen, R. T., 1985, Extraneous expert information, J. Forecast. 4 ,329–348.CrossRefGoogle Scholar
  5. Clemen, R. T., 1987, Combining overlapping information, Mgmt. Sci. ,in press.Google Scholar
  6. Clemen, R. T., and Murphy, A. H., 1986a, Objective and subjective precipitation probability forecasts: statistical analysis of some interrelationships, Weather and Forecasting 1, 56–65.CrossRefGoogle Scholar
  7. Clemen, R. T., and Murphy, A. H., 1986b, Objective and subjective precipitation probability forecasts: improvements via calibration and combination, Weather and Forecasting 1 ,in press.Google Scholar
  8. Clemen, R. T., and Winkler, R. L., 1986, Combining economic forecasts, J. Bus. Econ. Stat. 4 ,39–46.CrossRefGoogle Scholar
  9. DeGroot, M. H., and Fienberg, S. E., 1982, Assessing probability assessors: calibration and refinement, in: “Statistical Decision Theory and Related Topics III,” S. S. Gupta and J. O. Berger, eds., Academic Press, New York, 291–314.Google Scholar
  10. DeGroot, M. H., and Fienberg, S. E., 1983, The comparison and evaluation of forecasters, The Statistician 32 ,12–22.CrossRefGoogle Scholar
  11. French, S., 1980, Updating of belief in the light of someone else’s opinion, J. R. Statist. Soc. Ser. A 143 ,43–48.MathSciNetMATHCrossRefGoogle Scholar
  12. French, S., 1981, Consensus of opinion, Eur. J. Oper. Res. 7 ,332–340.MathSciNetMATHCrossRefGoogle Scholar
  13. French, S., 1985, Group consensus probability distributions: a critical survey, in: “Bayesian Statistics 2,” J. M. Bernardo, M. H. DeGroot, D. V. Lindley, and A. F. M. Smith, eds., North Holland, Amsterdam, 183–201.Google Scholar
  14. Genest, C., and Schervish, M. J, 1985, Modeling expert judgments for Bayesian updating, Ann. Stat. 13 ,1198–1212.MathSciNetMATHCrossRefGoogle Scholar
  15. Genest, C., and Zidek, J. V., 1986, Combining probability distributions: a critique and an annotated bibliography, Stat. Sci . 1 ,114–148.MathSciNetCrossRefGoogle Scholar
  16. Lindley, D. V., 1982, The improvement of probability judgments, J. R. Statist. Soc. Ser. A 145 ,117–126.MathSciNetMATHCrossRefGoogle Scholar
  17. Lindley, D. V., 1983, Reconciliation of probability distributions, Oper. Res. 31 ,866–880.MathSciNetMATHCrossRefGoogle Scholar
  18. Lindley, D. V., 1985, Reconciliation pf discrete probability distributions, in: “Bayesian Statistics 2,” J. M. Bernardo, M. H. DeGroot, D. V. Lindley, and A. F. M. Smith, eds., North Holland, Amsterdam, 375–390.Google Scholar
  19. Lindley, D. V., Tversky, A., and Brown, R. V., 1979, On the reconciliation of probability assessments, J. R. Statist. Soc. Ser. A 142 ,146–180.MathSciNetMATHCrossRefGoogle Scholar
  20. Makridakis, S., and Winkler, R. L., 1983, Averages of forecasts: some empirical results, Mgmt. Sci . 29 ,987–996.CrossRefGoogle Scholar
  21. Morris, P. A., 1974, Decision analysis expert use, Mgmt. Sci . 20 ,1233–1241.MATHCrossRefGoogle Scholar
  22. Morris, P. A., 1977, Combining expert judgments: a Bayesian approach, Mgmt. Sci . 23, 679–693.MATHCrossRefGoogle Scholar
  23. Murphy, A. H., 1985, Probabilistic weather forecasting, in: “Probability, Statistics, and Decision Making in the Atmospheric Sciences,” A. H. Murphy and R. W. Katz, eds., Westview Press, Boulder, CO, 337–377.Google Scholar
  24. Murphy, A. H., and Sabin, T. E., 1986, Trends in the quality of National Weather Service forecasts, Weather and Forecasting 1,42–55.CrossRefGoogle Scholar
  25. Murphy, A. H., and Winkler, R. L., 1984, Probability forecasting in meteorology, J. Amer. Statist. Assoc. 79 ,489–500.CrossRefGoogle Scholar
  26. Winkler, R. L., 1981, Combining probability distributions from dependent information sources, Mgmt. Sci . 27 ,479–488.MATHCrossRefGoogle Scholar

Copyright information

© Plenum Press, New York 1987

Authors and Affiliations

  • Robert T. Clemen
    • 1
  • Robert L. Winkler
    • 2
  1. 1.College of BusinessUniversity of OregonEugeneUSA
  2. 2.Fuqua School of BusinessDuke UniversityDurhamUSA

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