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Scoring Rules for Continuous Probability Distributions

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Cited by:

  1. Luisa Bisaglia & Matteo Grigoletto, 2018. "A new time-varying model for forecasting long-memory series," Papers 1812.07295, arXiv.org.
  2. Papakonstantinou, A. & Rogers, A & Gerding, E. H. & Jennings, N. R., 2010. "Mechanism Design for the truthful elicitation of costly probabilistic estimates in Distributed Information Systems," MPRA Paper 43324, University Library of Munich, Germany.
  3. Markus Heinrich & Magnus Reif, 2018. "Forecasting using mixed-frequency VARs with time-varying parameters," ifo Working Paper Series 273, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  4. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
  5. Glenn W. Harrison & Andre Hofmeyr & Harold Kincaid & Brian Monroe & Don Ross & Mark Schneider & J. Todd Swarthout, 2022. "Subjective beliefs and economic preferences during the COVID-19 pandemic," Experimental Economics, Springer;Economic Science Association, vol. 25(3), pages 795-823, June.
  6. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
  7. Di Girolamo, Amalia & Harrison, Glenn W. & Lau, Morten I. & Swarthout, J. Todd, 2015. "Subjective belief distributions and the characterization of economic literacy," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 59(C), pages 1-12.
  8. 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.
  9. Gensler, André & Sick, Bernhard & Vogt, Stephan, 2018. "A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 352-379.
  10. Matteo Iacopini & Francesco Ravazzolo & Luca Rossini, 2020. "Proper scoring rules for evaluating asymmetry in density forecasting," Papers 2006.11265, arXiv.org, revised Sep 2020.
  11. Lee Tae-Hwy & Wang He & Xi Zhou & Zhang Ru, 2023. "Density Forecast of Financial Returns Using Decomposition and Maximum Entropy," Journal of Econometric Methods, De Gruyter, vol. 12(1), pages 57-83, January.
  12. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
  13. Wang, Qin & Tuohy, Aidan & Ortega-Vazquez, Miguel & Bello, Mobolaji & Ela, Erik & Kirk-Davidoff, Daniel & Hobbs, William B. & Ault, David J. & Philbrick, Russ, 2023. "Quantifying the value of probabilistic forecasting for power system operation planning," Applied Energy, Elsevier, vol. 343(C).
  14. Hardaker, J. B., 1982. "Fundamental Aspects Of Risk And Uncertainty In Agriculture," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 21(2), October.
  15. Tilmann Gneiting & Larissa Stanberry & Eric Grimit & Leonhard Held & Nicholas Johnson, 2008. "Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(2), pages 211-235, August.
  16. Sungchul Hong & Jong-June Jeon, 2023. "Uniform Pessimistic Risk and Optimal Portfolio," Papers 2303.07158, arXiv.org.
  17. Krüger, Fabian & Pavlova, Lora, 2019. "Quantifying subjective oncertainty in survey expectations," Working Papers 0664, University of Heidelberg, Department of Economics.
  18. Mastrantonio, Gianluca, 2018. "The joint projected normal and skew-normal: A distribution for poly-cylindrical data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 14-26.
  19. Crosetto, Paolo & Filippin, Antonio & Katuščák, Peter & Smith, John, 2020. "Central tendency bias in belief elicitation," Journal of Economic Psychology, Elsevier, vol. 78(C).
  20. Song, Haiyan & Wen, Long & Liu, Chang, 2019. "Density tourism demand forecasting revisited," Annals of Tourism Research, Elsevier, vol. 75(C), pages 379-392.
  21. Xuesong Zhang & Kaiguang Zhao, 2012. "Bayesian Neural Networks for Uncertainty Analysis of Hydrologic Modeling: A Comparison of Two Schemes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(8), pages 2365-2382, June.
  22. Lemos-Vinasco, Julian & Bacher, Peder & Møller, Jan Kloppenborg, 2021. "Probabilistic load forecasting considering temporal correlation: Online models for the prediction of households’ electrical load," Applied Energy, Elsevier, vol. 303(C).
  23. Fang, Fang & Stinchcombe, Maxwell B. & Whinston, Andrew B., 2010. "Proper scoring rules with arbitrary value functions," Journal of Mathematical Economics, Elsevier, vol. 46(6), pages 1200-1210, November.
  24. Thomas W. Keelin & Bradford W. Powley, 2011. "Quantile-Parameterized Distributions," Decision Analysis, INFORMS, vol. 8(3), pages 206-219, September.
  25. Luisa Bisaglia & Matteo Grigoletto, 2021. "A new time-varying model for forecasting long-memory series," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 139-155, March.
  26. Tommaso Proietti & Martyna Marczak & Gianluigi Mazzi, 2017. "Euromind‐ D : A Density Estimate of Monthly Gross Domestic Product for the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 683-703, April.
  27. Lei Zhang & Lun Xie & Qinkai Han & Zhiliang Wang & Chen Huang, 2020. "Probability Density Forecasting of Wind Speed Based on Quantile Regression and Kernel Density Estimation," Energies, MDPI, vol. 13(22), pages 1-24, November.
  28. Bjørnland, Hilde C. & Gerdrup, Karsten & Jore, Anne Sofie & Smith, Christie & Thorsrud, Leif Anders, 2011. "Weights and pools for a Norwegian density combination," The North American Journal of Economics and Finance, Elsevier, vol. 22(1), pages 61-76, January.
  29. Ricardo Crisóstomo, 2021. "Estimating real‐world probabilities: A forward‐looking behavioral framework," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(11), pages 1797-1823, November.
  30. Jenny Brynjarsdottir & Jonathan Hobbs & Amy Braverman & Lukas Mandrake, 2018. "Optimal Estimation Versus MCMC for $$\mathrm{{CO}}_{2}$$ CO 2 Retrievals," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(2), pages 297-316, June.
  31. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
  32. Amalia Di Girolamo & Glenn W. Harrison & Morten I. Lau & J. Todd Swarthout, 2013. "Characterizing Financial and Statistical Literacy," Experimental Economics Center Working Paper Series 2013-04, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University.
  33. 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.
  34. Aragón, Nicolás & Roulund, Rasmus Pank, 2020. "Confidence and decision-making in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 688-718.
  35. Gross, Marco, 2011. "Corporate bond spreads and real activity in the euro area - Least Angle Regression forecasting and the probability of the recession," Working Paper Series 1286, European Central Bank.
  36. 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.
  37. Shiyu Han & Lan Wu & Yuan Cheng, 2016. "Equity Market Impact Modeling: an Empirical Analysis for Chinese Market," Papers 1610.08767, arXiv.org.
  38. Ferretti, Valentina & Guney, Sule & Montibeller, Gilberto & Winterfeldt, Detlof von, 2016. "Testing best practices to reduce the overconfidence bias in multi-criteria decision analysis," LSE Research Online Documents on Economics 67179, London School of Economics and Political Science, LSE Library.
  39. Mikuláš Gangur & Miroslav Plevný, 2014. "Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(36), pages 578-578, May.
  40. Hardaker, J. Brian & Lien, Gudbrand, 2010. "Probabilities for decision analysis in agriculture and rural resource economics: The need for a paradigm change," Agricultural Systems, Elsevier, vol. 103(6), pages 345-350, July.
  41. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd & Ulm, Eric R., 2015. "Eliciting subjective probability distributions with binary lotteries," Economics Letters, Elsevier, vol. 127(C), pages 68-71.
  42. Ricardo Crisóstomo & Lorena Couso, 2018. "Financial density forecasts: A comprehensive comparison of risk‐neutral and historical schemes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 589-603, August.
  43. 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.
  44. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd & Ulm, Eric R., 2017. "Scoring rules for subjective probability distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 430-448.
  45. David J. Eckman & Shane G. Henderson & Sara Shashaani, 2023. "Diagnostic Tools for Evaluating and Comparing Simulation-Optimization Algorithms," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 350-367, March.
  46. Tomás Marinozzi, 2023. "Forecasting Inflation in Argentina: A Probabilistic Approach," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(81), pages 81-110, May.
  47. Allen, P. Geoffrey & Morzuch, Bernard J., 1995. "Comparing probability forecasts derived from theoretical distributions," International Journal of Forecasting, Elsevier, vol. 11(1), pages 147-157, March.
  48. David S. Ching & Cosmin Safta & Thomas A. Reichardt, 2021. "Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters," Energies, MDPI, vol. 14(9), pages 1-21, April.
  49. Nico Keilman, 2020. "Evaluating Probabilistic Population Forecasts," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 520-521, pages 49-64.
  50. Tryggvi Jónsson & Pierre Pinson & Henrik Madsen & Henrik Aalborg Nielsen, 2014. "Predictive Densities for Day-Ahead Electricity Prices Using Time-Adaptive Quantile Regression," Energies, MDPI, vol. 7(9), pages 1-25, August.
  51. Victor Richmond R. Jose & Robert F. Nau & Robert L. Winkler, 2009. "Sensitivity to Distance and Baseline Distributions in Forecast Evaluation," Management Science, INFORMS, vol. 55(4), pages 582-590, April.
  52. Ander Wilson & David M. Reif & Brian J. Reich, 2014. "Hierarchical dose–response modeling for high-throughput toxicity screening of environmental chemicals," Biometrics, The International Biometric Society, vol. 70(1), pages 237-246, March.
  53. Marczak, Martyna & Proietti, Tommaso & Grassi, Stefano, 2018. "A data-cleaning augmented Kalman filter for robust estimation of state space models," Econometrics and Statistics, Elsevier, vol. 5(C), pages 107-123.
  54. Tae-Ho Kang & Ashish Sharma & Lucy Marshall, 2021. "Assessing Goodness of Fit for Verifying Probabilistic Forecasts," Forecasting, MDPI, vol. 3(4), pages 1-11, October.
  55. Carol Alexander & Michael Coulon & Yang Han & Xiaochun Meng, 2021. "Evaluating the Discrimination Ability of Proper Multivariate Scoring Rules," Papers 2101.12693, arXiv.org.
  56. 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.
  57. Steffen Andersen & John Fountain & Glenn Harrison & E. Rutström, 2014. "Estimating subjective probabilities," Journal of Risk and Uncertainty, Springer, vol. 48(3), pages 207-229, June.
  58. Markus Eyting & Patrick Schmidt, 2019. "Belief Elicitation with Multiple Point Predictions," Working Papers 1818, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz, revised 16 Nov 2020.
  59. 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.
  60. Robert L. Winkler & Yael Grushka-Cockayne & Kenneth C. Lichtendahl Jr. & Victor Richmond R. Jose, 2019. "Probability Forecasts and Their Combination: A Research Perspective," Decision Analysis, INFORMS, vol. 16(4), pages 239-260, December.
  61. Eyting, Markus & Schmidt, Patrick, 2021. "Belief elicitation with multiple point predictions," European Economic Review, Elsevier, vol. 135(C).
  62. Fabian Kruger & Hendrik Plett, 2022. "Prediction intervals for economic fixed-event forecasts," Papers 2210.13562, arXiv.org, revised Mar 2024.
  63. Yuan, Ying & Zhang, Tonghui, 2020. "Forecasting stock market in high and low volatility periods: a modified multifractal volatility approach," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
  64. Stephen C. Hora, 2004. "Probability Judgments for Continuous Quantities: Linear Combinations and Calibration," Management Science, INFORMS, vol. 50(5), pages 597-604, May.
  65. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  66. Mikkel L. Sørensen & Peter Nystrup & Mathias B. Bjerregård & Jan K. Møller & Peder Bacher & Henrik Madsen, 2023. "Recent developments in multivariate wind and solar power forecasting," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
  67. Michaël Zamo & Liliane Bel & Olivier Mestre, 2021. "Sequential aggregation of probabilistic forecasts—Application to wind speed ensemble forecasts," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 202-225, January.
  68. Robu, Valentin & Chalkiadakis, Georgios & Kota, Ramachandra & Rogers, Alex & Jennings, Nicholas R., 2016. "Rewarding cooperative virtual power plant formation using scoring rules," Energy, Elsevier, vol. 117(P1), pages 19-28.
  69. Victor Richmond R. Jose & Robert L. Winkler, 2009. "Evaluating Quantile Assessments," Operations Research, INFORMS, vol. 57(5), pages 1287-1297, October.
  70. Georgios Anastasiades & Patrick McSharry, 2013. "Quantile Forecasting of Wind Power Using Variability Indices," Energies, MDPI, vol. 6(2), pages 1-34, February.
  71. Schlag, Karl H. & van der Weele, Joël J., 2015. "A method to elicit beliefs as most likely intervals," Judgment and Decision Making, Cambridge University Press, vol. 10(5), pages 456-468, September.
  72. Stephen Hora & Erim Kardeş, 2015. "Calibration, sharpness and the weighting of experts in a linear opinion pool," Annals of Operations Research, Springer, vol. 229(1), pages 429-450, June.
  73. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
  74. Li, Yanting & Peng, Xinghao & Zhang, Yu, 2022. "Forecasting methods for wind power scenarios of multiple wind farms based on spatio-temporal dependency structure," Renewable Energy, Elsevier, vol. 201(P1), pages 950-960.
  75. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
  76. Victor Jose, 2009. "A Characterization for the Spherical Scoring Rule," Theory and Decision, Springer, vol. 66(3), pages 263-281, March.
  77. Thordis L. Thorarinsdottir & Tilmann Gneiting, 2010. "Probabilistic forecasts of wind speed: ensemble model output statistics by using heteroscedastic censored regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 371-388, April.
  78. 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.
  79. Richard Arsenault & Marco Latraverse & Thierry Duchesne, 2016. "An Efficient Method to Correct Under-Dispersion in Ensemble Streamflow Prediction of Inflow Volumes for Reservoir Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4363-4380, September.
  80. Ferretti, Valentina & Montibeller, Gilberto & von Winterfeldt, Detlof, 2023. "Testing the effectiveness of debiasing techniques to reduce overprecision in the elicitation of subjective continuous probability distributions," LSE Research Online Documents on Economics 115333, London School of Economics and Political Science, LSE Library.
  81. Alexander Henzi & Johanna F. Ziegel & Tilmann Gneiting, 2021. "Isotonic distributional regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 963-993, November.
  82. Theo S. Eicher & Chris Papageorgiou & Adrian E. Raftery, 2011. "Default priors and predictive performance in Bayesian model averaging, with application to growth determinants," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(1), pages 30-55, January/F.
  83. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
  84. Heinrich, Markus, 2020. "Does the Current State of the Business Cycle matter for Real-Time Forecasting? A Mixed-Frequency Threshold VAR approach," EconStor Preprints 219312, ZBW - Leibniz Information Centre for Economics.
  85. Bermejo Mancera, Miguel Ángel & Peña, Daniel & Sánchez, Ismael, 2011. "Densidad de predicción basada en momentos condicionados y máxima entropía : aplicación a la predicción de potencia eólica," DES - Working Papers. Statistics and Econometrics. WS ws111813, Universidad Carlos III de Madrid. Departamento de Estadística.
  86. D. Johnstone, 2007. "The Value of a Probability Forecast from Portfolio Theory," Theory and Decision, Springer, vol. 63(2), pages 153-203, September.
  87. Jozef Barunik & Lubos Hanus, 2022. "Learning Probability Distributions in Macroeconomics and Finance," Papers 2204.06848, arXiv.org.
  88. Jakob W. Messner & Georg J. Mayr & Daniel S. Wilks & Achim Zeileis, 2013. "Extending Extended Logistic Regression for Ensemble Post-Processing: Extended vs. Separate vs. Ordered vs. Censored," Working Papers 2013-32, Faculty of Economics and Statistics, Universität Innsbruck.
  89. Yael Grushka-Cockayne & Kenneth C. Lichtendahl Jr. & Victor Richmond R. Jose & Robert L. Winkler, 2017. "Quantile Evaluation, Sensitivity to Bracketing, and Sharing Business Payoffs," Operations Research, INFORMS, vol. 65(3), pages 712-728, June.
  90. Alvaro Sandroni & Eran Shmaya, 2013. "Eliciting beliefs by paying in chance," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 1(1), pages 33-37, May.
  91. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207, April.
  92. Fabian Krüger, 2017. "Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms," Empirical Economics, Springer, vol. 53(1), pages 235-246, August.
  93. Christopher P. Chambers & Nicolas S. Lambert, 2021. "Dynamic Belief Elicitation," Econometrica, Econometric Society, vol. 89(1), pages 375-414, January.
  94. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
  95. Bansal, Prateek & Krueger, Rico & Graham, Daniel J., 2021. "Fast Bayesian estimation of spatial count data models," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  96. Reinhard Selten, 1998. "Axiomatic Characterization of the Quadratic Scoring Rule," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 43-61, June.
  97. Krüger, Fabian & Nolte, Ingmar, 2016. "Disagreement versus uncertainty: Evidence from distribution forecasts," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 172-186.
  98. Barbaglia, Luca & Frattarolo, Lorenzo & Onorante, Luca & Pericoli, Filippo Maria & Ratto, Marco & Tiozzo Pezzoli, Luca, 2023. "Testing big data in a big crisis: Nowcasting under Covid-19," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1548-1563.
  99. Catania, Leopoldo & Luati, Alessandra, 2020. "Robust estimation of a location parameter with the integrated Hogg function," Statistics & Probability Letters, Elsevier, vol. 164(C).
  100. Cheng Peng & Stanislav Uryasev, 2023. "Factor Model of Mixtures," Papers 2301.13843, arXiv.org, revised Mar 2023.
  101. Silius M. Vandeskog & Sara Martino & Daniela Castro-Camilo & Håvard Rue, 2022. "Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(4), pages 598-621, December.
  102. Tim Janke & Florian Steinke, 2020. "Probabilistic multivariate electricity price forecasting using implicit generative ensemble post-processing," Papers 2005.13417, arXiv.org.
  103. Glenn Harrison & Karlijn Morsink & Mark Schneider, 2022. "Literacy and the quality of index insurance decisions," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 66-97, March.
  104. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2014. "Eliciting subjective probabilities with binary lotteries," Journal of Economic Behavior & Organization, Elsevier, vol. 101(C), pages 128-140.
  105. Konrad Bogner & Florian Pappenberger & Massimiliano Zappa, 2019. "Machine Learning Techniques for Predicting the Energy Consumption/Production and Its Uncertainties Driven by Meteorological Observations and Forecasts," Sustainability, MDPI, vol. 11(12), pages 1-22, June.
  106. Baran, Sándor & Lerch, Sebastian, 2018. "Combining predictive distributions for the statistical post-processing of ensemble forecasts," International Journal of Forecasting, Elsevier, vol. 34(3), pages 477-496.
  107. Papakonstantinou, A. & Rogers, A. & Gerding, E. H. & Jennings, N. R, 2008. "A Truthful Two-Stage Mechanism for Eliciting Probabilistic Estimates with Unknown Costs," MPRA Paper 43320, University Library of Munich, Germany.
  108. repec:cup:judgdm:v:10:y:2015:i:5:p:456-468 is not listed on IDEAS
  109. Steffen Andersen & John Fountain & Glenn Harrison & Arne Hole & E. Rutström, 2012. "Inferring beliefs as subjectively imprecise probabilities," Theory and Decision, Springer, vol. 73(1), pages 161-184, July.
  110. Pic, Romain & Dombry, Clément & Naveau, Philippe & Taillardat, Maxime, 2023. "Distributional regression and its evaluation with the CRPS: Bounds and convergence of the minimax risk," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1564-1572.
  111. Gneiting, Tilmann, 2011. "Quantiles as optimal point forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 197-207.
  112. Marie Courbariaux & Pierre Barbillon & Éric Parent, 2017. "Water flow probabilistic predictions based on a rainfall–runoff simulator: a two-regime model with variable selection," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(2), pages 194-219, June.
  113. repec:exc:wpaper:2013-05 is not listed on IDEAS
  114. Ferretti, Valentina & Montibeller, Gilberto & von Winterfeldt, Detlof, 2023. "Testing the effectiveness of debiasing techniques to reduce overprecision in the elicitation of subjective continuous probability distributions," European Journal of Operational Research, Elsevier, vol. 304(2), pages 661-675.
  115. Dieppe, Alistair & van Roye, Björn & Legrand, Romain, 2016. "The BEAR toolbox," Working Paper Series 1934, European Central Bank.
  116. Tavana, Madjid & Di Caprio, Debora, 2016. "Modeling synergies in multi-criteria supplier selection and order allocation: An application to commodity tradingAuthor-Name: Sodenkamp, Mariya A," European Journal of Operational Research, Elsevier, vol. 254(3), pages 859-874.
  117. Nicholls, Nicky, 2023. "Procrastination and grades: Can students be nudged towards better outcomes?," International Review of Economics Education, Elsevier, vol. 42(C).
  118. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.
  119. Pedro Henrique Melo Albuquerque & Yaohao Peng & João Pedro Fontoura da Silva, 2022. "Making the whole greater than the sum of its parts: A literature review of ensemble methods for financial time series forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1701-1724, December.
  120. 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.
  121. Emilio Porcu & Philip A. White, 2022. "Random fields on the hypertorus: Covariance modeling and applications," Environmetrics, John Wiley & Sons, Ltd., vol. 33(1), February.
  122. Cameron J. Williams & Kevin J. Wilson & Nina Wilson, 2021. "A comparison of prior elicitation aggregation using the classical method and SHELF," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 920-940, July.
  123. Joanne Ellison & Erengul Dodd & Jonathan J. Forster, 2020. "Forecasting of cohort fertility under a hierarchical Bayesian approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 829-856, June.
  124. Silius M. Vandeskog & Thordis L. Thorarinsdottir & Ingelin Steinsland & Finn Lindgren, 2022. "Quantile based modeling of diurnal temperature range with the five‐parameter lambda distribution," Environmetrics, John Wiley & Sons, Ltd., vol. 33(4), June.
  125. de Haan, Thomas, 2020. "Eliciting belief distributions using a random two-level partitioning of the state space," Working Papers in Economics 1/20, University of Bergen, Department of Economics.
  126. Alvaro Sandroni & Eran Shmaya, 2013. "Eliciting Beliefs by Paying in Chance," Discussion Papers 1565, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
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