Order Estimation and Discrimination Between Stationary and Time-Varying (TVAR) Autoregressive Models

  title={Order Estimation and Discrimination Between Stationary and Time-Varying (TVAR) Autoregressive Models},
  author={Yuri I. Abramovich and Nicholas K. Spencer and Michael D. E. Turley},
  journal={IEEE Transactions on Signal Processing},
For a set of T independent observations of the same N-variate correlated Gaussian process, we derive a method of estimating the order of an autoregressive (AR) model of this process, regardless of its stationary or time-varying nature. We also derive a test to discriminate between stationary AR models of order m,AR(m), and time-varying autoregressive models of order m,TVAR(m). We demonstrate that within this technique the number T of independent identically distributed data samples required for… CONTINUE READING
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Tables of Integrals

  • I. Gradshteyn, I. Ryzhik
  • Series, and Products, 6th ed. New York: Academic
  • 2000
Highly Influential
4 Excerpts

Distribution of the likelihood ratio criterion for testing a hypothesis specifying a covariance matrix,

  • B. Nagarsenker, K. Pillai
  • Biometrica, vol. 60,
  • 2007
Highly Influential
3 Excerpts

Digital Processing of Random Signals

  • B. Porat
  • 5th ed. Englewood Cliffs, NJ: Prentice-Hall
  • 1994
Highly Influential
4 Excerpts

Algorithms for maximum likelihood constrained covariance estimation,” presented at the CSSIP Short Courses

  • E. Polak
  • 2001
2 Excerpts

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