if (FALSE) {
## Generate Population Model and Monte Carlo Samples ####
sout <- simFA(Model = list(NFac = 5,
NItemPerFac = 5,
Model = "orthogonal"),
Loadings = list(FacLoadDist = "fixed",
FacLoadRange = .8),
MonteCarlo = list(NSamples = 100,
SampleSize = 500),
Seed = 655342)
## Population EFA loadings
(True_A <- sout$loadings)
## Population Phi matrix
sout$Phi
## Compute EFA on Sample 67 ####
fout <- faMain (R = sout$Monte$MCData[[67]],
numFactors = 5,
targetMatrix = sout$loadings,
facMethod = "fals",
rotate= "cfT",
rotateControl = list(numberStarts = 50,
standardize="CM",
kappa = 1/25),
Seed=3366805)
## Summarize output from faMain
summary(fout, Set = 1, DiagnosticsLevel = 2, digits=4)
## Investigate Local Solutions
LMout <- faLocalMin(fout,
Set = 1,
HPthreshold = .15,
digits= 5,
PrintLevel = 1)
## Print hyperplane count for each factor pattern
## in the solution set
LMout$HPcount
}
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