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Portable Network Graphic  |  1994-04-29  |  72KB  |  816x1056  |  8-bit (256 colors)
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OCR: The Eigenstructure table is useful for identifying the shape and orientation of the curvature and results from the eigenvalue decomposition of the matrix of second-order parameter estimates The eigenvalues are positive if the surface shape curves an from unique minimum. If the eigenvalues are mixed, the surface is saddle-shaped, curving dn in one direction and down in another direction. The eigenvalues are negative if the response surface shap curves back from unigue maximum. Sometimes a zero EiaenStructure eigenvalue occurs This EigenValues and EigenVectors means that along the Variable 48 3803 30. 6004 direction described by the temp 0.23892 0.97104 corresponding eigenvector, gl ratio 0.97104 -0.23892 fitted surface flat. the directior