The conditioning of the maximum entropy covariance matrix and its inverse

Delores Conway and Henri Theil

Statistics & Probability Letters, 1982, vol. 1, issue 2, 103-106

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.

Keywords: Condition; numbers; covariance; matrix; estimation; entropy; latent; roots; ridge; matrices (search for similar items in EconPapers)
Date: 1982
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