Spectral Condition Numbers of Orthogonal Projections and Full Rank Linear Least Squares Residuals

  • Authors:
  • Joseph F. Grcar

  • Affiliations:
  • jfgrcar@comcast.net

  • Venue:
  • SIAM Journal on Matrix Analysis and Applications
  • Year:
  • 2010

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Abstract

A simple formula is proved to be a tight estimate for the condition number of the full rank linear least squares residual with respect to the matrix of least squares coefficients and scaled 2-norms. The tight estimate reveals that the condition number depends on three quantities, two of which can cause ill-conditioning. The numerical linear algebra literature presents several estimates of various instances of these condition numbers. All the prior values exceed the formula introduced here, sometimes by large factors.