Nonstationary, and Strongly Dependent Normal Sequences

  • M. R. Leadbetter
  • Georg Lindgren
  • Holger Rootzén
Part of the Springer Series in Statistics book series (SSS)

Abstract

While our primary concern in this volume is with stationary processes, the results and methods may be used to apply simply to some important nonstationary cases. In particular, this is so for nonstationary normal sequences having a wide variety of possible mean and correlation structures, which is the situation considered first in this chapter.

Keywords

Covariance Convolution 

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Copyright information

© Springer-Verlag New York Inc. 1983

Authors and Affiliations

  • M. R. Leadbetter
    • 1
  • Georg Lindgren
    • 2
  • Holger Rootzén
    • 3
  1. 1.Department of StatisticsThe University of North CarolinaChapel HillUSA
  2. 2.Department of Mathematical StatisticsUniversity of LundLundSweden
  3. 3.Institute of Mathematical StatisticsUniversity of CopenhagenCopenhagen øDenmark

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