TY - JOUR
T1 - Statistical analysis of autoregressive fractionally integrated moving average models in R
AU - Contreras-Reyes, Javier E.
AU - Palma, Wilfredo
PY - 2013/10
Y1 - 2013/10
N2 - 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.
AB - 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.
KW - ARFIMA models
KW - Exact variance matrix
KW - Forecasting
KW - Impulse response functions
KW - Long-memory time series
KW - R
KW - Whittle estimation
UR - http://www.scopus.com/inward/record.url?scp=84884701605&partnerID=8YFLogxK
U2 - 10.1007/s00180-013-0408-7
DO - 10.1007/s00180-013-0408-7
M3 - Article
AN - SCOPUS:84884701605
SN - 0943-4062
VL - 28
SP - 2309
EP - 2331
JO - Computational Statistics
JF - Computational Statistics
IS - 5
ER -