Order selection of autoregressive models

  • Authors:
  • P.M. Djuric;S.M. Kay

  • Affiliations:
  • Dept. of Electr. Eng., State Univ. of New York, Stony Brook, NY;-

  • Venue:
  • IEEE Transactions on Signal Processing
  • Year:
  • 1992

Quantified Score

Hi-index 35.68

Visualization

Abstract

The problem of determining the order of autoregressive models by Bayesian predictive densities is addressed. A criterion employing noninformative prior densities of the model parameters is derived. Simulation results which demonstrate the good performance of the criterion are presented. Comparisons with four popular approaches verify its superiority in many cases