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:

References in zbMATH (referenced in 110 articles , 1 standard article )

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  1. Taieb, Souhaib Ben; Taylor, James W.; Hyndman, Rob J.: Hierarchical probabilistic forecasting of electricity demand with smart meter data (2021)
  2. 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)
  3. Bajalinov, E.; Duleba, Sz.: Seasonal time series forecasting by the Walsh-transformation based technique (2020)
  4. Basellini, Ugofilippo; Kjærgaard, Søren; Camarda, Carlo Giovanni: An age-at-death distribution approach to forecast cohort mortality (2020)
  5. Bildosola, Iñaki; Garechana, Gaizka; Zarrabeitia, Enara; Cilleruelo, Ernesto: Characterization of strategic emerging technologies: the case of big data (2020)
  6. Bozikas, Apostolos; Pitselis, Georgios: Incorporating crossed classification credibility into the Lee-Carter model for multi-population mortality data (2020)
  7. Esam Mahdi: portes: An R Package for Portmanteau Tests in Time Series Models (2020) arXiv
  8. Izhar Asael Alonzo Matamoros, Alicia Nieto-Reyes: An R package for Normality in Stationary Processes (2020) arXiv
  9. Izhar Asael Alonzo Matamoros, Cristian Andres Cruz Torres: varstan: An R package for Bayesian analysis of structured time series models with Stan (2020) arXiv
  10. Li, Degui; Robinson, Peter M.; Shang, Han Lin: Long-range dependent curve time series (2020)
  11. Li, Yang; Zhu, Zhengyuan: Spatio-temporal modeling of global ozone data using convolution (2020)
  12. Lowther, Aaron P.; Fearnhead, Paul; Nunes, Matthew A.; Jensen, Kjeld: Semi-automated simultaneous predictor selection for regression-SARIMA models (2020)
  13. Marina Knight, Kathryn Leeming, Guy Nason, Matthew Nunes: Generalized Network Autoregressive Processes and the GNAR Package (2020) not zbMATH
  14. Neeraj Dhanraj Bokde; Gorm Bruun Andersen: ForecastTB - An R Package as a Test-bench for Forecasting Methods Comparison (2020) arXiv
  15. Nystrup, Peter; Lindström, Erik; Pinson, Pierre; Madsen, Henrik: Temporal hierarchies with autocorrelation for load forecasting (2020)
  16. Shang, Han Lin: Dynamic principal component regression for forecasting functional time series in a group structure (2020)
  17. Shang, Han Lin; Haberman, Steven: Forecasting multiple functional time series in a group structure: an application to mortality (2020)
  18. Spiliotis, Evangelos; Assimakopoulos, Vassilios; Makridakis, Spyros: Generalizing the Theta method for automatic forecasting (2020)
  19. Wickramasuriya, Shanika L.; Turlach, Berwin A.; Hyndman, Rob J.: Optimal non-negative forecast reconciliation (2020)
  20. Annette Möller, Jürgen Groß: Probabilistic Temperature Forecasting with a Heteroscedastic Autoregressive Ensemble Postprocessing model (2019) arXiv

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