IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v31y1966i2p125-145.html
   My bibliography  Save this article

Admissible probability measurement procedures

Author

Listed:
  • Emir Shuford
  • Arthur Albert
  • H. Edward Massengill

Abstract

No abstract is available for this item.

Suggested Citation

  • Emir Shuford & Arthur Albert & H. Edward Massengill, 1966. "Admissible probability measurement procedures," Psychometrika, Springer;The Psychometric Society, vol. 31(2), pages 125-145, June.
    • Handle: RePEc:spr:psycho:v:31:y:1966:i:2:p:125-145
    DOI: 10.1007/BF02289503
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02289503
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02289503?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. R. Winkler & Javier Muñoz & José Cervera & José Bernardo & Gail Blattenberger & Joseph Kadane & Dennis Lindley & Allan Murphy & Robert Oliver & David Ríos-Insua, 1996. "Scoring rules and the evaluation of probabilities," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 1-60, June.
    2. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
    3. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    4. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    5. Francesco Giancaterini & Alain Hecq & Claudio Morana, 2022. "Is Climate Change Time-Reversible?," Econometrics, MDPI, vol. 10(4), pages 1-18, December.
    6. Pamela Giustinelli & Charles F. Manski, 2018. "Survey Measures Of Family Decision Processes For Econometric Analysis Of Schooling Decisions," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 81-99, January.
    7. Karl Schlag & James Tremewan & Joël Weele, 2015. "A penny for your thoughts: a survey of methods for eliciting beliefs," Experimental Economics, Springer;Economic Science Association, vol. 18(3), pages 457-490, September.
    8. Jingni Yang, 2020. "The uniqueness of local proper scoring rules: the logarithmic family," Theory and Decision, Springer, vol. 88(2), pages 315-322, March.
    9. Roberto Leon-Gonzalez & Blessings Majoni, 2023. "Exact Likelihood for Inverse Gamma Stochastic Volatility Models," Working Paper series 23-11, Rimini Centre for Economic Analysis.
    10. Robert Clemen, 2002. "Incentive contrats and strictly proper scoring rules," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 11(1), pages 167-189, June.
    11. Victor Jose, 2009. "A Characterization for the Spherical Scoring Rule," Theory and Decision, Springer, vol. 66(3), pages 263-281, March.
    12. J. Eric Bickel, 2007. "Some Comparisons among Quadratic, Spherical, and Logarithmic Scoring Rules," Decision Analysis, INFORMS, vol. 4(2), pages 49-65, June.
    13. J. Eric Bickel, 2010. "Scoring Rules and Decision Analysis Education," Decision Analysis, INFORMS, vol. 7(4), pages 346-357, December.
    14. Lambert, Nicolas S. & Langford, John & Wortman Vaughan, Jennifer & Chen, Yiling & Reeves, Daniel M. & Shoham, Yoav & Pennock, David M., 2015. "An axiomatic characterization of wagering mechanisms," Journal of Economic Theory, Elsevier, vol. 156(C), pages 389-416.
    15. Xu, Hao & Gardoni, Paolo, 2020. "Conditional formulation for the calibration of multi-level random fields with incomplete data," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    16. Andrew Caplin & Daniel Martin & Philip Marx, 2022. "Calibrating for Class Weights by Modeling Machine Learning," Papers 2205.04613, arXiv.org, revised Jul 2022.
    17. Miller, Nolan & Resnick, Paul & Zeckhauser, Richard, 2002. "Eliciting Honest Feedback in Electronic Markets," Working Paper Series rwp02-039, Harvard University, John F. Kennedy School of Government.
    18. Werner Ehm & Tilmann Gneiting & Alexander Jordan & Fabian Krüger, 2016. "Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 505-562, June.
    19. George Duncan, 1978. "Binary action based estimation of propensities," Psychometrika, Springer;The Psychometric Society, vol. 43(1), pages 93-107, March.
    20. Kenneth C. Lichtendahl & Yael Grushka-Cockayne & Robert L. Winkler, 2013. "Is It Better to Average Probabilities or Quantiles?," Management Science, INFORMS, vol. 59(7), pages 1594-1611, July.
    21. Yanwei Jia & Jussi Keppo & Ville Satopää, 2023. "Herding in Probabilistic Forecasts," Management Science, INFORMS, vol. 69(5), pages 2713-2732, May.
    22. D. J. Hand & C. Anagnostopoulos, 2023. "Notes on the H-measure of classifier performance," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(1), pages 109-124, March.
    23. George Duncan & E. Milton, 1978. "Multiple-answer multiple-choice test items: Responding and scoring through bayes and minimax strategies," Psychometrika, Springer;The Psychometric Society, vol. 43(1), pages 43-57, March.
    24. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:psycho:v:31:y:1966:i:2:p:125-145. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.