Autoregressive Moving-Average Models

Klaus Neusser ()

Chapter 2 in Time Series Econometrics, 2016, pp 25-44 from Springer

Abstract: Abstract A basic idea in time series analysis is to construct more complex processes from simple ones. In the previous chapter we showed how the averaging of a white noise process leads to a process with first order autocorrelation. In this chapter we generalize this idea and consider processes which are solutions of linear stochastic difference equations. These so-called ARMA processes constitute the most widely used class of models for stationary processes.

Keywords: Difference Equation; Autocorrelation Function; Equation System; Impulse Response Function; ARMA Model (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-319-32862-1_2

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DOI: 10.1007/978-3-319-32862-1_2

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