Description Usage Arguments Details Value Author(s) References Examples
View source: R/GreaterLowerBound.R
Estimates the communalities of the variables from a factor model where the number of factors is the number with positive eigenvalues.
1 | GreaterLowerBound(C, conv = 0.000001, T, pwarnings = FALSE)
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C |
Covariance/correlation matrix to be used in the analysis. |
conv |
Convergence criterion for glb step. The default convergence criterion will be conv=0.000001 . If the user determine a specific value, this will prevail. |
T |
Random matrix for start (can be omitted). If provided, it has to be the same size than the matrix provided in the C argument. |
pwarnings |
Determines if the possible warnings occurred during the computation will be printed in the console. |
Code adapted from a MATLAB function by Jos Ten Berge based on Ten Berge, Snijders & Zegers (1981) and Ten Berge & Kiers (1991).
gam |
Optimal communalities for each variable |
David Navarro-Gonzalez
Urbano Lorenzo-Seva
Ten Berge, J.M.F., & Kiers, H.A.L. (1991). A numerical approach to the exact and the approximate minimum rank of a covariance matrix. Psychometrika, 56, 309-315.
Ten Berge, J.M.F., Snijders, T.A.B. & Zegers, F.E. (1981). Computational aspects of the greatest lower bound to reliability and constrained minimum trace factor analysis. Psychometrika, 46, 201-213.
1 2 3 | ## perform glb using the correlation matrix of the IDAQ dataset, and using severe convergence
## criterion.
GreaterLowerBound(cor(IDAQ), conv=0.000001)
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