Document Type
Article
Department/Program
Mathematics
Journal Title
Computational Economics
Pub Date
3-2014
Publisher
Springer
Volume
43
Issue
3
First Page
313
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.
Recommended Citation
Webb, Keith H. and Leemis, Lawrence, Symbolic ARMA Model Analysis (2014). Computational Economics, 43(3), 313-330.
https://doi.org/10.1007/s10614-013-9373-z
DOI
https://doi.org/10.1007/s10614-013-9373-z
Publisher Statement
This version is the accepted (post-print) version of the manuscript.
