Advertisement

Further Topics

  • Peter J. Brockwell
  • Richard A. Davis
Part of the Springer Series in Statistics book series (SSS)

Abstract

In this final chapter we touch on a variety of topics of special interest The Kaiman recursions have had a profound impact in time series analysis and in many related areas. In Section 12.1 the basic recursions are derived and applied to ARMA processes with observational noise. A similar analysis is used in Sections 12.3 and 12.7 to deal with data having unequally spaced (or missing) values. In Section 12.2 we consider transfer function models, designed to exploit, for predictive purposes, the relationship between two time series when one leads the other. Section 12.4 deals with long-memory models, characterized by very slow convergence to zero of the autocorrelations ρ(h) as h → ∞. Such models are suggested by numerous observed series in hydrology and economics. In Section 12.5 we examine linear time-series models with infinite variance and in Section 12.6 we briefly consider non-linear models and their applications.

Keywords

Threshold Model ARMA Model Transfer Function Model Infinite Variance ARMA Process 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media New York 1987

Authors and Affiliations

  • Peter J. Brockwell
    • 1
  • Richard A. Davis
    • 1
  1. 1.Department of StatisticsColorado State UniversityFort CollinsUSA

Personalised recommendations