Corpus ID: 236772327

Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale

@article{Papacharalampous2021MassiveFE,
  title={Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale},
  author={Georgia Papacharalampous and Hristos Tyralis and Ilias G. Pechlivanidis and Salvatore Grimaldi and Elena Volpi},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.00846}
}
Statistical analyses and descriptive characterizations are sometimes assumed to be offering information on time series forecastability. Despite the scientific interest suggested by such assumptions, the relationships between descriptive time series features (e.g., temporal dependence, entropy, seasonality, trend and nonlinearity features) and actual time series forecastability (quantified by issuing and assessing forecasts for the past) are scarcely studied and quantified in the literature. In… Expand

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