Symbolic ARMA Model Analysis

John H. Drew, Diane L. Evans, Andrew G. Glen and Lawrence M. Leemis
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John H. Drew: The College of William and Mary
Diane L. Evans: Rose-Hulman Institute of Technology
Andrew G. Glen: Colorado College
Lawrence M. Leemis: The College of William and Mary

Chapter 11 in Computational Probability, 2017, pp 191-208 from Springer

Abstract: Abstract This chapter extends the APPL language to include the analysis of ARMA (autoregressive moving average) time series models. 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 oftentimes tedious to compute by hand, and APPL can help ease the computational burden.

Keywords: Error Term; Autocorrelation Function; Time Series Model; ARMA Model; Autoregressive Moving Average (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-43323-3_11

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