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Autoregressive Hilbertian Processes of Order 1

  • Denis Bosq
Chapter
  • 788 Downloads
Part of the Lecture Notes in Statistics book series (LNS, volume 149)

Abstract

In this chapter we particularize the representation of a continuous-time process as a sequence of B-random variables (recall Figure 1). Actually, we consider the case where B is a Hilbert space and the induced discrete time process is a linear Markov sequence. This leads to define the autoregressive Hilbertian process of order 1, denoted ARH(1), a flexible model that is used in practice to model and predict continuous-time random experiments (see Chapter 9).

Keywords

Hilbert Space White Noise Limit Theorem Markov Process Innovation 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.

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Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Denis Bosq
    • 1
  1. 1.Institut de StatistiqueUniversité Pierre et Marie CurieParis Cedex 05France

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