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Spectral Theory

  • D. J. Daley
  • D. Vere-Jones
Part of the Springer Series in Statistics book series (SSS)

Abstract

The spectral theory of point processes and random measures is concerned with frequency (i.e., Fourier) representations of various kinds and degrees of generality. In this chapter we look first at the frequency representation of the reduced second-order measures introduced in Chapter 10 and then at frequency representations and related questions for the process itself. Such representations have less value in the present context than in the continuous (especially, Gaussian) context, for reasons already touched on in previous chapters: the mean square representations rarely preserve the character of the original trajectories of the process, and the linear predictors to which they give rise can often be improved upon by quite simple nonlinear predictors (cf Chapter 13).

Keywords

Point Process Spectral Measure Spectral Theory Random Measure Covariance Measure 
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.

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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • D. J. Daley
    • 1
  • D. Vere-Jones
    • 2
  1. 1.Department of Statistics Institute for Advanced StudyAustralian National UniversityCanberraAustralia
  2. 2.Department of StatisticsVictoria UniversityWellingtonNew Zealand

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