The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Automatic Time Series Forecasting: The forecast Package for R
Open accessAbstract
Automatic forecasts of large numbers of univariate time series are often needed in business and other contexts. We describe two automatic forecasting algorithms that have been implemented in the forecast package for R. The first is based on innovations state space models that underly exponential smoothing methods. The second is a step-wise algorithm for forecasting with ARIMA models. The algorithms are applicable to both seasonal and non-seasonal data, and are compared and illustrated using four real time series. We also briefly describe some of the other functionality available in the forecast package.
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Cites
Testing the null hypothesis of stationarity against the alternative of a unit root
Kwiatkowski, D., Phillips, P. C. B., Schmidt, P., & Shin, Y. (1992) · Journal of Econometrics · doi:10.1016/0304-4076(92)90104-y · Cited by 12,633
Another look at measures of forecast accuracy
Hyndman, R. J., & Koehler, A. B. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.03.001 · Cited by 5,757
Self-citation
Cited by
Statistical and machine learning forecasting methods: Concerns and ways forward
Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018) · PLOS ONE · doi:10.1371/journal.pone.0194889 · Cited by 1,528
Recurrent Neural Networks for Time Series Forecasting: Current status and future directions
Hewamalage, H., Bergmeir, C., & Bandara, K. (2021) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2020.06.008 · Cited by 1,371
Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing
De Livera, A. M., Hyndman, R. J., & Snyder, R. D. (2011) · Journal of the American Statistical Association · doi:10.1198/jasa.2011.tm09771 · Cited by 1,049
Self-citationHost lifestyle affects human microbiota on daily timescales
David, L. A., Materna, A. C., Friedman, J., Campos-Baptista, M. I., Blackburn, M. C., Perrotta, A., Erdman, S. E., & Alm, E. J. (2014) · Genome biology · doi:10.1186/gb-2014-15-7-r89 · Cited by 950
Predicting Taxi–Passenger Demand Using Streaming Data
Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., & Damas, L. (2013) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2013.2262376 · Cited by 721
Metadata
- Authors
- Hyndman, R. J., & Khandakar, Y.
- Venue
- Journal of Statistical Software
- Publisher
- Foundation for Open Access Statistic
- Published
- 2008
- Volume
- 27
- Issue
- 3
- ISSN
- 1548-7660 (ISSN-L)
- OpenAlex
- W2116512828
- Cited by
- 3,511
- References
- 2
- FWCI
- 30.24
- Type
- journal article
- Language
- en
- Open access
- diamond
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