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Global Combinations of Expert Forecasts
SSRN Electronic Journal, 2022Expert forecast combination—the aggregation of individual forecasts from multiple subjectmatter experts— is a proven approach to economic forecasting. To date, research in this area has exclusively concentrated on local combination methods, which handle separate but related forecasting tasks in isolation.
Qian, Yilin +2 more
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Combining forecasts: An application to elections
International Journal of Forecasting, 2014Abstract We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections,
Andreas Graefe +3 more
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2001
To improve forecasting accuracy, combine forecasts derived from methods that differ substantially and draw from different sources of information. When feasible, use five or more methods. Use formal procedures to combine forecasts: An equal-weights rule offers a reasonable starting point, and a trimmed mean is desirable if you combine forecasts ...
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To improve forecasting accuracy, combine forecasts derived from methods that differ substantially and draw from different sources of information. When feasible, use five or more methods. Use formal procedures to combine forecasts: An equal-weights rule offers a reasonable starting point, and a trimmed mean is desirable if you combine forecasts ...
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Dynamic selection of forecast combiners
Neurocomputing, 2016Time series forecasting is an important research field in machine learning. Since the literature shows several techniques for the solution of this problem, combining outputs of different models is a simple and robust strategy. However, even when using combiners, the experimenter may face the following dilemma: which technique should one use to combine ...
Anderson Tenório Sergio +2 more
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Combination of Multi Level Forecasts
The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 2007This paper provides a discussion of the effects of different multi-level learning approaches on the resulting out of sample forecast errors in the case of difficult real-world forecasting problems with large noise terms in the training data, frequently occurring structural breaks and quickly changing environments.
Silvia Riedel, Bogdan Gabrys
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Forecast evaluation and forecast combination
2010Diese Arbeit ist zweigeteilt. Im ersten Teil werden Institute, die sich an der Prognose zentraler, ökonomischer Kennzahlen beteiligen, auf ihre Prognosegenauigkeit hin untersucht. Zu diesem Zweck wurde ein Datensatz erstellt, der BIP-Prognosen für Großbritannien von ca. 50 verschiedenen Instituten über die letzten 11 Jahre zusammenfasst.
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Some Comments on the Combination of Forecasts
Operational Research Quarterly (1970-1977), 1975This paper examines some of the theoretical implications of combining forecasts using a minimum variance criterion. In particular, the derivation of the exact expression for the minimum variance weight vector is provided, together with a proof that the error variance of the composite forecast is no greater than that of any of the component forecasts. A
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Combination and selection of binary forecasts
IEEE Transactions on Systems, Man, and Cybernetics, 1991Binary yes-no forecasts are used to indicate whether a particular set of events will or will not occur. A mechanism for combining independent binary forecasts for the case where likelihood functions are available is given. The decision maker (DM) has to assume a priori from the natural conjugate family of distributions, and uses the forecasts as data ...
G. Anandalingam, Lian Chen
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Pooling for Combination of Multilevel Forecasts
IEEE Transactions on Knowledge and Data Engineering, 2009In this paper, we provide a theoretical analysis of effects of applying different forecast diversification methods on the structure of the forecast error covariance matrices and decomposed forecast error components based on the bias-variance-Bayes error decomposition of James and Hastie. We express the "diversityrdquo of different forecasts in relation
Silvia Riedel, Bogdan Gabrys
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The Combination of Forecasts: a Bayesian Approach
Journal of the Operational Research Society, 1982This paper develops a general Bayesian approach to the problem of combining forecasts. This approach leads to the results of Bates and Granger in certain special cases and to a geometric averaging formula in other special cases.
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