Degenerate Multivariate Stationary Processes: Basicity, Past and Future, and Autoregressive Representation.

Abstract

An important problem in prediction theory of weakly stationary stochastic processes (WSSP) is to find conditions on the process, or equivalently on its spectral distribution F, so that the linear least square predictor of a future value of the process admits a mean-convergent series representation in terms of the past (observed) values of the process. Recently, using the notion of positivity of the angle between the past-present and the future subspaces of the process it was shown by Pourahmadi that the series representation of the predictor is possible under some weaker conditions. This was made possible by using the idea of angle due to Helson and Szego for a multivariate extension of this. However these results hold under conditions which require the process to be full rank. The main purpose of this document is to consider the same problem, including their autoregressive representation, for the degenerate WSSP's. Additional keywords: Moving average representation.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1985
Accession Number
ADA158879

Entities

People

  • A. G. Miamee
  • M. Pourahmadi

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Banach Space
  • Concrete
  • Convergence
  • Data Science
  • Infinite Series
  • Information Science
  • North Carolina
  • Probability
  • Random Variables
  • Sequences
  • Stationary
  • Stationary Processes
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • Time Domain
  • Universities

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Quantum Chemistry
  • Statistical inference.