Abstract
ARMA models provide a parsimonious and flexible mechanism for modeling the evolution of a time series. Some useful measures of these models (e.g., the autocorrelation function or the spectral density function) are tedious to compute by hand. This paper uses a computer algebra system, not simulation, to calculate measures of interest associated with ARMA models.
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The extension can be downloaded from http://www.math.wm.edu/~leemis/TSAPPL.txt and APPL can be downloaded from http://applsoftware.com/
References
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Woodward, W. A., & Gray, H. L. (1981). On the relationship between the S array and the Box–Jenkins method of ARMA model identification. Journal of the American Statistical Association, 76(375), 579–587.
Acknowledgments
This research is partially supported by an NSF CSUMS Grant DMS–0703532 at the College of William & Mary.
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Webb, K.H., Leemis, L.M. Symbolic ARMA Model Analysis. Comput Econ 43, 313–330 (2014). https://doi.org/10.1007/s10614-013-9373-z
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DOI: https://doi.org/10.1007/s10614-013-9373-z