What are condition numbers and why are they important?
The ratio of the largest eigenvalue to the smallest eigenvalue, referred to as the condition number, is a measure of ill-conditioning. Eigenvalues are generated by NONMEM when the PRINT=E argument is used in the $COVARIANCE record. A condition number exceeding 1 000 is indicative of severe ill-conditioning (Montgomery DC, Peck EA. Introduction to Linear Regression Analysis. Wiley, NY, 1982, pp. 301-302). Thanks to William Bachman for this definition, which I’ve shamelessly stolen.
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