Forecast

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.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 94 articles )

Showing results 1 to 20 of 94.
Sorted by year (citations)

1 2 3 4 5 next

  1. Wei, Baolei; Xie, Naiming: On unified framework for continuous-time grey models: an integral matching perspective (2022)
  2. Arnerić, Josip: Multiple STL decomposition in discovering a multi-seasonality of intraday trading volume (2021)
  3. Cadena, Meitner; Denuit, Michel: A new measure of mortality differentials based on precedence probability (2021)
  4. Eckert, Florian; Hyndman, Rob J.; Panagiotelis, Anastasios: Forecasting Swiss exports using Bayesian forecast reconciliation (2021)
  5. Goel, Anubha; Mehra, Aparna: Robust omega ratio optimization using regular vines (2021)
  6. Kourentzes, Nikolaos; Athanasopoulos, George: Elucidate structure in intermittent demand series (2021)
  7. Ma, Shaohui; Fildes, Robert: Retail sales forecasting with meta-learning (2021)
  8. Ollech, Daniel: Seasonal adjustment of daily time series (2021)
  9. Sanna Passino, Francesco; Bertiger, Anna S.; Neil, Joshua C.; Heard, Nicholas A.: Link prediction in dynamic networks using random dot product graphs (2021)
  10. Taieb, Souhaib Ben; Taylor, James W.; Hyndman, Rob J.: Hierarchical probabilistic forecasting of electricity demand with smart meter data (2021)
  11. Van Belle, Jente; Guns, Tias; Verbeke, Wouter: Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains (2021)
  12. Zhao, Xin; Barber, Stuart; Taylor, Charles C.; Milan, Zoka: Interval forecasts based on regression trees for streaming data (2021)
  13. 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)
  14. Atance, David; Balbás, Alejandro; Navarro, Eliseo: Constructing dynamic life tables with a single-factor model (2020)
  15. Bajalinov, E.; Duleba, Sz.: Seasonal time series forecasting by the Walsh-transformation based technique (2020)
  16. Bildosola, Iñaki; Garechana, Gaizka; Zarrabeitia, Enara; Cilleruelo, Ernesto: Characterization of strategic emerging technologies: the case of big data (2020)
  17. Bozikas, Apostolos; Pitselis, Georgios: Incorporating crossed classification credibility into the Lee-Carter model for multi-population mortality data (2020)
  18. Li, Degui; Robinson, Peter M.; Shang, Han Lin: Long-range dependent curve time series (2020)
  19. Li, Yang; Zhu, Zhengyuan: Spatio-temporal modeling of global ozone data using convolution (2020)
  20. Lowther, Aaron P.; Fearnhead, Paul; Nunes, Matthew A.; Jensen, Kjeld: Semi-automated simultaneous predictor selection for regression-SARIMA models (2020)

1 2 3 4 5 next