| FactorAnalysisGetValues Method |
Returns the eigenvalues.
Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.2.0
SyntaxReturn Value
Type: DoubleA double array containing the eigenvalues of the matrix from which the factors were extracted ordered from largest to smallest.
Exceptions| Exception | Condition |
|---|---|
| RankException | is thrown if the rank of the covariance matrix is less than the number of factors. |
| NotSemiDefiniteException | is thrown if the Hessian matrix not semi-definite. |
| NotPositiveSemiDefiniteException | is thrown if the covariance matrix is not positive semi-definite. |
| SingularException | is thrown if the covariance matrix is singular. |
| BadVarianceException | is thrown if the input variance is not in the allowed range. |
| EigenvalueException | is thrown if an error occured in calculating the eigenvalues of the adjusted (inverse) covariance matrix. Check the input covariance matrix. |
| NonPositiveEigenvalueException | is thrown if in alpha factor analysis an eigenvalue is not positive. As all eigenvalues corresponding to the factors must be positive, either the number of factors must be reduced, or new initial estimates for the unique variances must be given. |
Remarks
If Alpha Factor analysis is used, then the first nfactors
positions of the array contain the Alpha coefficients. Here,
nfactors is the number of factors in the model. If the
algorithm fails to converge for a particular eigenvalue, that
eigenvalue is set to NaN. Note that the eigenvalues are
usually not the eigenvalues of the input matrix cov. They are the
eigenvalues of the input matrix cov when the Principal Component
method is used.
See Also