Statistical analysis of autoregressive fractionally integrated moving average models in R

Javier Contreras-Reyes () and Wilfredo Palma ()

Computational Statistics, 2013, vol. 28, issue 5, 2309-2331

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. Copyright Springer-Verlag Berlin Heidelberg 2013

Keywords: ARFIMA models; Long-memory time series; Whittle estimation; Exact variance matrix; Impulse response functions; Forecasting; R (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:28:y:2013:i:5:p:2309-2331

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DOI: 10.1007/s00180-013-0408-7

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