Angular Combining of Forecasts of Probability Distributions
References
- (2019) The evolution of forecast density combinations in economics. Oxford Research Encyclopedia of Economics and Finance (Oxford University Press, Oxford, UK).Crossref, Google Scholar
- (2020) Special report: The simulations driving the world’s response to covid-19. Nature 580(7802):316–319.Crossref, Google Scholar
- (1951) Optimal inventory policy. Econometrica 19(3):250–272.Crossref, Google Scholar
- (2016) A commentary on “how to interpret expert judgment assessments of twenty-first century sea-level rise” by Hylke de Vries and Roderik SW van de Wal. Climate Change 137(3):321–328.Crossref, Google Scholar
- (2021) Evaluating epidemic forecasts in an interval format. PLOS Comput. Biol. 17(2):e1008618.Crossref, Google Scholar
- (2021) Backtesting global growth-at-risk. J. Monetary Econom. 118:312–330.Crossref, Google Scholar
- (2017) Quantile aggregation of density forecasts. Oxford Bull. Econom. Statist. 79(4):495–512.Crossref, Google Scholar
- (2010) Quantile and probability curves without crossing. Econometrica 78(3):1093–1125.Crossref, Google Scholar
- (2012) Elements of Financial Risk Management, 2nd ed. (Academic Press, Waltham, MA).Google Scholar
- (2018) Are macroeconomic density forecasts informative? Internat. J. Forecasting 34(2):181–198.Crossref, Google Scholar
- (2017) Cross validation for the classical model of structured expert judgment. Reliability Engrg. System Safety 163:109–120.Crossref, Google Scholar
- (2023) Averaging quantiles, variance shrinkage, and overconfidence. Futures Foresight Sci. 5:e139.Crossref, Google Scholar
- (2021) Expert forecasting with and without uncertainty quantification and weighting: What do the data say? Internat. J. Forecasting 37(1):378–387.Crossref, Google Scholar
- (2023) Flexible model aggregation for quantile regression. J. Machine Learn. Res. 24(162):1–45.Google Scholar
- (2006) Tests of conditional predictive ability. Econometrica 74(6):1545–1578.Crossref, Google Scholar
- (2007) Strictly proper scoring rules, prediction, and estimation. J. Amer. Statist. Assoc. 102(477):359–378.Crossref, Google Scholar
- (2013) Combining predictive distributions. Electronic J. Statist. 7:1747–1782.Crossref, Google Scholar
- (2017a) Ensembles of overfit and overconfident forecasts. Management Sci. 63(4):1110–1130.Link, Google Scholar
- (2017b) Quantile evaluation, sensitivity to bracketing, and sharing business payoffs. Oper. Res. 65(3):712–728.Link, Google Scholar
- (2007) Combining density forecasts. Internat. J. Forecasting 23(1):1–13.Crossref, Google Scholar
- (2022) Recalibrating probabilistic forecasts to improve their accuracy. Judgment Decision Making 17(1):91–123.Crossref, Google Scholar
- (2004) Probability judgments for continuous quantities: Linear combinations and calibration. Management Sci. 50(5):597–604.Link, Google Scholar
- (2013) Median aggregation of distribution functions. Decision Anal. (Oxford) 10(4):279–291.Link, Google Scholar
- (2009) Evaluating quantile assessments. Oper. Res. 57(5):1287–1297.Link, Google Scholar
- (2014) Trimmed opinion pools and the crowd’s calibration problem. Management Sci. 60(2):463–475.Link, Google Scholar
- (2015) Generalised density forecast combinations. J. Econometrics 188(1):150–165.Crossref, Google Scholar
- (2022) Forecast uncertainty, disagreement, and the linear pool. J. Appl. Econometrics 37(1):23–41.Crossref, Google Scholar
- (2012) The social psychology of the wisdom of crowds. Krueger JI, ed. Frontiers in Social Psychology: Social Judgment and Decision Making (Psychology Press, New York), 227–242.Google Scholar
- (2013) Is it better to average probabilities or quantiles? Management Sci. 59(7):1594–1611.Link, Google Scholar
- (2022) The M5 uncertainty competition: Results, findings and conclusions. Internat. J. Forecasting 38(4):1365–1385.Crossref, Google Scholar
- (2020) Probabilistic electricity price forecasting with Narx networks: Combine point or probabilistic forecasts? Internat. J. Forecasting 36(2):466–479.Crossref, Google Scholar
- (2008) The trouble with overconfidence. Psych. Rev. 115(2):502.Crossref, Google Scholar
- (2018) Recent advances in electricity price forecasting: A review of probabilistic forecasting. Renewable Sustainable Energy Rev. 81:1548–1568.Crossref, Google Scholar
- (2005) Using Bayesian model averaging to calibrate forecast ensembles. Monthly Weather Rev. 133(5):1155–1174.Crossref, Google Scholar
- (2023) Comparing trained and untrained probabilistic ensemble forecasts of covid-19 cases and deaths in the united states. Internat. J. Forecasting 39(3):1366–1383.Crossref, Google Scholar
- (2024) Overconfidence in probability distributions: People know they don’t know, but they don’t know what to do about it. Management Sci. 70(11):7422–7442.Link, Google Scholar
- (1998) A comparison of linear and nonlinear univariate models for forecasting macroeconomic time series. NBER Working Paper No. 6607, National Bureau of Economic Research, Cambridge, MA.Google Scholar
- (1961) The opinion pool. Ann. Math. Statist. 32(4):1339–1342.Crossref, Google Scholar
- (2004) The Wisdom of Crowds: Why the Many Are Smarter than the Few (Doubleday, New York).Google Scholar
- (2021) Evaluating quantile-bounded and expectile-bounded interval forecasts. Internat. J. Forecasting 37(2):800–811.Crossref, Google Scholar
- (2018) Probabilistic forecasting of wave height for offshore wind turbine maintenance. Eur. J. Oper. Res. 267(3):877–890.Crossref, Google Scholar
- (2023) Combining probabilistic forecasts of Covid-19 mortality in the United States. Eur. J. Oper. Res. 304(1):25–41.Crossref, Google Scholar
- (2022) Interval forecasts of weekly incident and cumulative covid-19 mortality in the united states: A comparison of combining methods. PLOS One 17(3):e0266096.Crossref, Google Scholar
- (1980) On appropriate procedures for combining probability distributions within the same family. J. Math. Psych. 21(2):136–152.Crossref, Google Scholar
- (2021) Regularized quantile regression averaging for probabilistic electricity price forecasting. Energy Econom. 95:105121.Crossref, Google Scholar
- (2019) On the importance of the long-term seasonal component in day-ahead electricity price forecasting: Part II: Probabilistic forecasting. Energy Econom. 79:171–182.Crossref, Google Scholar
- (2024) CRPS-based online learning for nonlinear probabilistic forecast combination. Internat. J. Forecasting 40(4):1449–1466.Crossref, Google Scholar
- (2021) An axiomatic foundation for the expected shortfall. Management Sci. 67(3):1413–1429.Link, Google Scholar
- (2019) Probability forecasts and their combination: A research perspective. Decision Anal. (Oxford) 16(4):239–260.Link, Google Scholar
- (2019) Call center arrivals: When to jointly forecast multiple streams? Production Oper. Management 28(1):27–42.Crossref, Google Scholar

