forecast

R package forecast: Forecasting functions for time series and linear models , Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling. (Source: http://cran.r-project.org/web/packages)


References in zbMATH (referenced in 130 articles , 1 standard article )

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  1. Wei, Baolei; Xie, Naiming: On unified framework for continuous-time grey models: an integral matching perspective (2022)
  2. Adithi R. Upadhya, Pratyush Agrawal, Sreekanth Vakacherla, Meenakshi Kushwaha: pollucheck v1.0: A package to explore open-source air pollution data (2021) not zbMATH
  3. Ben O’Neill: Gaussian ARMA models in the ts.extend package (2021) arXiv
  4. David Salinas, Valentin Flunkert, Jan Gasthaus: DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks (2021) arXiv
  5. Eckert, Florian; Hyndman, Rob J.; Panagiotelis, Anastasios: Forecasting Swiss exports using Bayesian forecast reconciliation (2021)
  6. Goel, Anubha; Mehra, Aparna: Robust Omega ratio optimization using regular vines (2021)
  7. Klaus Nordhausen, Markus Matilainen, Jari Miettinen, Joni Virta, Sara Taskinen: Dimension Reduction for Time Series in a Blind Source Separation Context Using R (2021) not zbMATH
  8. Kourentzes, Nikolaos; Athanasopoulos, George: Elucidate structure in intermittent demand series (2021)
  9. Lange, Henning; Brunton, Steven L.; Kutz, J. Nathan: From Fourier to Koopman: spectral methods for long-term time series prediction (2021)
  10. Li, Yicheng; Raftery, Adrian E.: Accounting for smoking in forecasting mortality and life expectancy (2021)
  11. Ma, Shaohui; Fildes, Robert: Retail sales forecasting with meta-learning (2021)
  12. Michał Narajewski, Jens Kley-Holsteg, Florian Ziel: tsrobprep - an R package for robust preprocessing of time series data (2021) arXiv
  13. Ollech, Daniel: Seasonal adjustment of daily time series (2021)
  14. Peder Bacher, Hjörleifur G. Bergsteinsson, Linde Frölke, Mikkel L. Sørensen, Julian Lemos-Vinasco, Jon Liisberg, Jan Kloppenborg Møller, Henrik Aalborg Nielsen, Henrik Madsen: onlineforecast: An R package for adaptive and recursive forecasting (2021) arXiv
  15. Taieb, Souhaib Ben; Taylor, James W.; Hyndman, Rob J.: Hierarchical probabilistic forecasting of electricity demand with smart meter data (2021)
  16. Van Belle, Jente; Guns, Tias; Verbeke, Wouter: Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains (2021)
  17. Zhao, Xin; Barber, Stuart; Taylor, Charles C.; Milan, Zoka: Interval forecasts based on regression trees for streaming data (2021)
  18. Alexandrov, Alexander; Benidis, Konstantinos; Bohlke-Schneider, Michael; Flunkert, Valentin; Gasthaus, Jan; Januschowski, Tim; Maddix, Danielle C.; Rangapuram, Syama; Salinas, David; Schulz, Jasper; Stella, Lorenzo; Türkmen, Ali Caner; Wang, Yuyang: GluonTS: probabilistic and neural time series modeling in Python (2020)
  19. Atance, David; Balbás, Alejandro; Navarro, Eliseo: Constructing dynamic life tables with a single-factor model (2020)
  20. Bajalinov, E.; Duleba, Sz.: Seasonal time series forecasting by the Walsh-transformation based technique (2020)

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