| factor.model {psych} | R Documentation | 
The basic factor or principal components model is that a correlation or covariance matrix may be reproduced by the product of a factor loading matrix times its transpose.  Find this reproduced matrix.  Used by factor.fit, VSS, ICLUST, etc.
factor.model(f,Phi=NULL,U2=TRUE)
f | 
 A matrix of loadings.  | 
Phi | 
 A matrix of factor correlations  | 
U2 | 
 Should the diagonal be model by ff' (U2 = TRUE) or replaced with 1's (U2 = FALSE)  | 
A correlation or covariance matrix.
revelle@northwestern.edu 
https://personality-project.org/revelle.html 
Gorsuch, Richard, (1983) Factor Analysis. Lawrence Erlebaum Associates. 
Revelle, W. In preparation) An Introduction to Psychometric Theory with applications in R (https://personality-project.org/r/book/) 
ICLUST.graph,ICLUST.cluster, cluster.fit , VSS, omega 
f2 <- matrix(c(.9,.8,.7,rep(0,6),.6,.7,.8),ncol=2)
mod <- factor.model(f2)
round(mod,2)