Time Series: Cycles

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This article discusses cyclical (or periodic) properties of stochastic processes. The spectrum (or spectral density function) is introduced as a method for characterizing the approximate periodic behavior of realizations from stochastic processes. The spectral representation is introduced as a way to decompose a stochastic process into its periodic components. Moving average filters change the cyclical properties of time series, and formulae characterizing these changes are developed. Specific moving average filters are discussed, and general formulae for extracting components associated with specific frequencies (bandpass filters) are presented. Spectral properties of ARMA process are derived. Methods for estimating spectra are outlined.

Original languageEnglish (US)
Title of host publicationInternational Encyclopedia of the Social & Behavioral Sciences: Second Edition
PublisherElsevier Inc.
Pages331-336
Number of pages6
ISBN (Electronic)9780080970875
ISBN (Print)9780080970868
DOIs
StatePublished - Mar 26 2015

All Science Journal Classification (ASJC) codes

  • Social Sciences(all)

Keywords

  • Special density function
  • Spectrum
  • Stochastic processes

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  • Cite this

    Watson, M. W. (2015). Time Series: Cycles. In International Encyclopedia of the Social & Behavioral Sciences: Second Edition (pp. 331-336). Elsevier Inc.. https://doi.org/10.1016/B978-0-08-097086-8.42183-5