Internal function for pfa.
factanal.fit.principal(cmat, factors, p = ncol(cmat), start = NULL,
iter.max = 10, unique.tol = 1e-04)provided correlation matrix
number of factors
number of observations
vector of start values
maximum number of iteration used to calculate the common factor
the tolerance for a deviation of the maximum (in each row, without the diag) value of the given correlation matrix to the new calculated value
A matrix of loadings, one column for each factor. The factors are ordered in decreasing order of sums of squares of loadings.
uniquness
correlation matrix
The results of the optimization: the value of the negativ log-likelihood and information of the iterations used.
the factors
degrees of freedom
"principal"
C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.