Time Series Models and Mathematica

Robert A. Stine

Chapter 16 in Economic and Financial Modeling with Mathematica®, 1993, pp 368-406 from Springer

Abstract: Abstract This notebook introduces a package of Mathematica functions that manipulate autoregressive, integrated moving average (ARIMA) models. ARIMA models describe discrete-time stochastic processes—time series. The models are most adept at modeling stationary processes. Through differencing, however, these models accommodate certain forms of nonstationary processes as well.

Keywords: Transfer Function; Spectral Density; Unit Circle; Time Series Model; ARMA Model (search for similar items in EconPapers)
Date: 1993
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DOI: 10.1007/978-1-4757-2281-9_16

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