eigenvalues


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eigenvalues

statistical term meaning latent root.
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In the limit case f = 0, the two remaining eigenvalues [[lambda].
There is another component which has eigenvalue more than 1, but this component is not presented in Table 1 because it doesn't contain more than two variables having loadings greater than 0.
Another possibility to deflate the part associated with the infinite eigenvalues is to use equivalence transformations that are unitary but not structure preserving.
If [lambda] is a complex eigenvalue of the matrix L, then [lambda] satisfies the discrete Euler-Lotka equation
Condition indices are the square roots of the ratio of the largest eigenvalue to each individual eigenvalue.
We do not know what the eigenvalues are, but these graphs are not in general strongly regular (as evidenced by the observation that they have more than 3 distinct eigenvalues).
Thus, there are at most two distinct eigenvalues of A.
A natural step is to perform an eigenvalue decomposition of D [2]
In [5] the same author studied the eigenvalues of the matrix S in dependence of the oversampling parameter and the number of missing samples; see also [6] for a related result.
Suppose on the contrary that A is positive definite, has distinct eigenvalues and [square root of A] [not equal to] [b.
1976) Eigenvalues and eigenvectors of symmetric centrosymmetric matrices, Linear Algebra Appl.