Model combinations through revised base rates
نویسندگان
چکیده
Standard selection criteria for forecasting models focus on information that is calculated each series independently, disregarding the general tendencies and performance of candidate models. In this paper, we propose a new way to perform statistical model combination incorporates base rates models, which are then revised so per-series taken into account. We examine two schemes based precision sensitivity from contingency table rates. apply our approach pools either exponential smoothing or ARMA considering both simulated real time series, show work better than standard benchmarks. test significance results, discuss connection other cross-learning approaches, offer insights regarding implications theory practice.
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ژورنال
عنوان ژورنال: International Journal of Forecasting
سال: 2023
ISSN: ['1872-8200', '0169-2070']
DOI: https://doi.org/10.1016/j.ijforecast.2022.07.010