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The conditioning of the maximum entropy covariance matrix and its inverse

Author

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  • Conway, Delores
  • Theil, Henri

Abstract

The maximum entropy covariance matrix is positive definite even when the number of variables p exceeds the sample size n. However, the inverse of this matrix can have stability problems when p is close to n, although these problems tend to disappear as p increases beyond n. We analyze such problems using the variance of the latent roots in a particular metric as a condition number.

Suggested Citation

  • Conway, Delores & Theil, Henri, 1982. "The conditioning of the maximum entropy covariance matrix and its inverse," Statistics & Probability Letters, Elsevier, vol. 1(2), pages 103-106, November.
    • Handle: RePEc:eee:stapro:v:1:y:1982:i:2:p:103-106
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