Advertisement

On Spectral Analysis of Stationary Time Series

  • Richard A. Davis
  • Keh-Shin Lii
  • Dimitris N. Politis
Chapter
Part of the Selected Works in Probability and Statistics book series (SWPS)

Abstract

The present statistical theory of analysis of stationary time series (e.g., extrapolation) has assumed complete knowledge of the covariance sequence or equivalently of the spectrum of the process. It is, therefore, of great importance to be able to estimate one of these. However, knowledge of the spectrum seems to yield greater immediate insight into the structure of the process. This seems to have first been noted in a fundamental paper by Bartlett.1 An unpublished paper by Tukey2 deals with some aspects of the problem of estimating the spectrum.

Keywords

Spectral Density Covariance Sequence Noise Color Complete Knowledge Confidence Band 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Richard A. Davis
    • 1
  • Keh-Shin Lii
    • 2
  • Dimitris N. Politis
    • 3
  1. 1.Department of StatisticsColumbia UniversityNew YorkUSA
  2. 2.Department of StatisticsUniversity of CaliforniaRiversideUSA
  3. 3.Department of MathematicsUniversity of California, San DiegoLa JollaUSA

Personalised recommendations