Stationarity and Linear Time Series Models

Víctor Gómez
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Víctor Gómez: Ministerio de Hacienda y Administraciones Públicas Dirección Gral. de Presupuestos, Subdirección Gral. de Análisis y P.E.

Chapter Chapter 3 in Multivariate Time Series With Linear State Space Structure, 2016, pp 113-211 from Springer

Abstract: Abstract In this chapter, the concepts of stochastic processes, time series, stationarity, ergodicity, time domain, frequency domain, and linear time invariant filters are introduced. The Wold decomposition for stationary models is presented. VARMA and innovations state space models are introduced and some of their properties are described. Several properties and algorithms for covariance generating functions and spectra are given. Recursive autoregressive fitting and partial autocorrelations for stationary processes are discussed.

Keywords: Innovations State Space Model; Linear Time-invariant Filter; VARMA Models; Levinson-Durbin Recursion; Partial Autocorrelation Coefficients (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-28599-3_3

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DOI: 10.1007/978-3-319-28599-3_3

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