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Confidence in estimated airframe costs : uncertainty assessment in aggregate predictions
Timson, Frederick Samuel - 1972
Persistent link: https://www.econbiz.de/10000636594
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Human judgement is heavy tailed : empirical evidence and implications for the aggregation of estimates and forecasts
Lobo, Miguel Sousa; Yao, Dai - 2010
Persistent link: https://www.econbiz.de/10008807692
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Simple robust tests for the specification of high-frequency predictors of a low-frequency series
Miller, J. Isaac - 2014
Persistent link: https://www.econbiz.de/10010403018
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Causality and forecasting in temporally aggregated multivariate GARCH processes
Hafner, Christian M. - In: The econometrics journal 12 (2009) 1, pp. 127-146
Persistent link: https://www.econbiz.de/10003841978
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Asymptotic forecasting error evaluation for estimated temporally aggregated linear processes
Grigoryeva, Lyudmila; Ortega, Juan-Pablo - In: International journal of computational economics and … 5 (2015) 3, pp. 289-318
Persistent link: https://www.econbiz.de/10011413834
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Temporal aggregation in diffusion models of first-time purchase : does choice of frequency matter?
Putsis, William P. - In: Technological forecasting & social change : an … 51 (1996) 3, pp. 265-279
Persistent link: https://www.econbiz.de/10001198595
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Bagging weak predictors
Hillebrand, Eric; Lukas, Manuel; Wei, Wei - In: International journal of forecasting 37 (2021) 1, pp. 237-254
Persistent link: https://www.econbiz.de/10012692700
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Bagging weak predictors
Hillebrand, Eric; Lukas, Manuel; Wei, Wei - 2020
Persistent link: https://www.econbiz.de/10012607673
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Forecasting aggregates and disaggregates with common features
Espasa Terrades, Antoni; Mayo-Burgos, Iván - In: International journal of forecasting 29 (2013) 4, pp. 718-732
Persistent link: https://www.econbiz.de/10010221293
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Nagging predictors
Richman, Ronald; Wüthrich, Mario V. - In: Risks : open access journal 8 (2020) 3/83, pp. 1-26
We define the nagging predictor, which, instead of using bootstrapping to produce a series of i.i.d. predictors, exploits the randomness of neural network calibrations to provide a more stable and accurate predictor than is available from a single neural network run. Convergence results for the...
Persistent link: https://www.econbiz.de/10012293262