Abstract
The autoregressive fractionally integrated moving average (ARFIMA) processes are one of the best-known classes of long-memory models. In the package afmtools for R, we have implemented a number of statistical tools for analyzing ARFIMA models. In particular, this package contains functions for parameter estimation, exact autocovariance calculation, predictive ability testing and impulse response function computation, among others. Furthermore, the implemented methods are illustrated with applications to real-life time series.
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Acknowledgments
Wilfredo Palma would like to thank the support from Fondecyt Grant 1120758. The authors thank the editor, the co-editor and an anonymous referee for their helpful comments and suggestions.
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Contreras-Reyes, J.E., Palma, W. Statistical analysis of autoregressive fractionally integrated moving average models in R. Comput Stat 28, 2309–2331 (2013). https://doi.org/10.1007/s00180-013-0408-7
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DOI: https://doi.org/10.1007/s00180-013-0408-7