References

All methods cite the original work or the software manual. No invented references — every entry below is verifiable.

Assimakopoulos, Vassilios, and Konstantinos Nikolopoulos. 2000. “The Theta Model: A Decomposition Approach to Forecasting.” International Journal of Forecasting.

Bollerslev, Tim. 1986. “Generalized Autoregressive Conditional Heteroskedasticity.” Journal of Econometrics.

Box, George E. P., and David R. Cox. 1964. “An Analysis of Transformations.” Journal of the Royal Statistical Society: Series B.

Box, George E. P., and Gwilym M. Jenkins. 1976. Time Series Analysis: Forecasting and Control. Holden-Day.

Chen, Tianqi, and Carlos Guestrin. 2016. “XGBoost: A Scalable Tree Boosting System.” In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Cleveland, Robert B., William S. Cleveland, Jean E. McRae, and Irma Terpenning. 1990. “STL: A Seasonal-Trend Decomposition Procedure Based on Loess.” Journal of Official Statistics.

Cortes, Corinna, and Vladimir Vapnik. 1995. “Support-Vector Networks.” Machine Learning.

Croston, John D. 1972. “Forecasting and Stock Control for Intermittent Demands.” Operational Research Quarterly.

Engle, Robert F. 1982. “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation.” Econometrica.

Friedman, Jerome, Trevor Hastie, and Robert Tibshirani. 2010. “Regularization Paths for Generalized Linear Models via Coordinate Descent.” Journal of Statistical Software.

Ghalanos, Alexios. 2024. Rugarch: Univariate GARCH Models. https://cran.r-project.org/package=rugarch.

Hyndman, Rob J., and George Athanasopoulos. 2021. Forecasting: Principles and Practice. 3rd ed. OTexts. https://otexts.com/fpp3/.

Hyndman, Rob J., George Athanasopoulos, Christoph Bergmeir, Gabriel Caceres, Leanne Chhay, Mitchell O’Hara-Wild, Fotios Petropoulos, Slava Razbash, Earo Wang, and Farah Yasmeen. 2025. Forecast: Forecasting Functions for Time Series and Linear Models. https://cran.r-project.org/package=forecast.

Hyndman, Rob J., and Ye Khandakar. 2008. “Automatic Time Series Forecasting: The Forecast Package for r.” Journal of Statistical Software.

Hyndman, Rob J., Anne B. Koehler, J. Keith Ord, Ralph D. Snyder, and Glen R. Grose. 2008. Forecasting with Exponential Smoothing: The State Space Approach. Springer.

Killick, Rebecca, and Idris A. Eckley. 2014. “Changepoint: An r Package for Changepoint Analysis.” Journal of Statistical Software.

Livera, Alysha M. De, Rob J. Hyndman, and Ralph D. Snyder. 2011. “Forecasting Time Series with Complex Seasonal Patterns Using Exponential Smoothing.” Journal of the American Statistical Association.

Nikolopoulos, Konstantinos, Aris A. Syntetos, John E. Boylan, Fotios Petropoulos, and Vassilios Assimakopoulos. 2011. “An Aggregate-Disaggregate Intermittent Demand Approach (ADIDA) to Forecasting: An Intermittent Demand Approach.” International Journal of Production Economics.

Pfaff, Bernhard. 2024. Vars: VAR Modelling. https://cran.r-project.org/package=vars.

Sims, Christopher A. 1980. “Macroeconomics and Reality.” Econometrica.

Syntetos, Aris A., and John E. Boylan. 2005. “The Accuracy of Intermittent Demand Estimates.” International Journal of Forecasting.

Taylor, Sean J., and Benjamin Letham. 2023. Prophet: Automatic Forecasting Procedure. https://cran.r-project.org/package=prophet.

Teunter, Ruud H., Aris A. Syntetos, and M. Zied Babai. 2011. “Intermittent Demand: Linking Forecasting to Inventory Obsolescence.” International Journal of Production Economics.

Trapletti, Adrian, and Kurt Hornik. 2024. Tseries: Time Series Analysis and Computational Finance. https://cran.r-project.org/package=tseries.

Venables, William N., and Brian D. Ripley. 2002. Modern Applied Statistics with s. 4th ed. Springer.

Wright, Marvin N., and Andreas Ziegler. 2017. “Ranger: A Fast Implementation of Random Forests for High Dimensional Data in c++ and r.” Journal of Statistical Software.