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 150 articles , 1 standard article )

Showing results 81 to 100 of 150.
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  1. Dellino, G.; Laudadio, T.; Mari, R.; Mastronardi, N.; Meloni, C.: Microforecasting methods for fresh food supply chain management: a computational study (2018)
  2. Ghodsi, Mansi; Hassani, Hossein; Rahmani, Donya; Silva, Emmanuel Sirimal: Vector and recurrent singular spectrum analysis: which is better at forecasting? (2018)
  3. Golyandina, Nina; Korobeynikov, Anton; Zhigljavsky, Anatoly: Singular spectrum analysis with R (2018)
  4. Imbert, Alyssa; Vialaneix, Nathalie: Exploring, handling, imputing and evaluating missing data in statistical analyses: a review of existing approaches (2018)
  5. Mair, Patrick: Modern psychometrics with R (2018)
  6. Norwood, Ben; Killick, Rebecca: Long memory and changepoint models: a spectral classification procedure (2018)
  7. Petropoulos, Fotios; Hyndman, Rob J.; Bergmeir, Christoph: Exploring the sources of uncertainty: why does bagging for time series forecasting work? (2018)
  8. Sagaert, Yves R.; Aghezzaf, El-Houssaine; Kourentzes, Nikolaos; Desmet, Bram: Tactical sales forecasting using a very large set of macroeconomic indicators (2018)
  9. Salas-Molina, Francisco; Rodríguez-Aguilar, Juan A.; Serrà, Joan; Guillen, Montserrat; Martin, Francisco J.: Empirical analysis of daily cash flow time-series and its implications for forecasting (2018)
  10. Stojanović, Vladica; Randjelović, Dragan; Kuk, Kristijan: Noise-indicator nonnegative integer-valued autoregressive time series of the first order (2018)
  11. Yuan Tang: Autoplotly - Automatic Generation of Interactive Visualizations for Popular Statistical Results (2018) arXiv
  12. Athanasopoulos, George; Hyndman, Rob J.; Kourentzes, Nikolaos; Petropoulos, Fotios: Forecasting with temporal hierarchies (2017)
  13. Ham, Seunghon; Kim, Sunju; Lee, Naroo; Kim, Pilje; Eom, Igchun; Lee, Byoungcheun; Tsai, Perng-Jy; Lee, Kiyoung; Yoon, Chungsik: Comparison of data analysis procedures for real-time nanoparticle sampling data using classical regression and ARIMA models (2017)
  14. Hassani, Hossein; Kalantari, Mahdi; Yarmohammadi, Masoud: An improved SSA forecasting result based on a filtered recurrent forecasting algorithm (2017)
  15. Hassani, Hossein; Silva, Emmanuel Sirimal; Ghodsi, Zara: Optimizing bicoid signal extraction (2017)
  16. Hassler, Michael: Heuristic decision rules for short-term trading of renewable energy with co-located energy storage (2017)
  17. Hua, Jia-Chen; Noorian, Farzad; Moss, Duncan; Leong, Philip H. W.; Gunaratne, Gemunu H.: High-dimensional time series prediction using kernel-based koopman mode regression (2017)
  18. Michis, Antonis A.; Nason, Guy P.: Case study: shipping trend estimation and prediction via multiscale variance stabilisation (2017)
  19. Pravilovic, Sonja; Bilancia, Massimo; Appice, Annalisa; Malerba, Donato: Using multiple time series analysis for geosensor data forecasting (2017)
  20. Sadaei, Hossein Javedani; Guimarães, Frederico Gadelha; José da Silva, Cidiney; Lee, Muhammad Hisyam; Eslami, Tayyebeh: Short-term load forecasting method based on fuzzy time series, seasonality and long memory process (2017)