r - Deriving/interpreting factor loadings from factor analysis -


trying factor analysis first time . have set of data representing closing prices of s&p index , 10 other stocks .when run scree test on data set(11 variables ) eigen value of 2 run factanal number of factors =2 , turns out p value low. bump number of factors until 6 after run numerical problems. assume should fail reject hypothesis number of factors 6.

now assuming ever have described above correct way proceed how derive factor loadings 6 factors ? comment able figure out factor loadings how interpret them ?

as can see lodings empty of factors.

these values :

loadings:        factor1  factor2  factor3 factor4 factor5 factor6   sp500  0.597    0.710    0.150   0.107   0.316          xom                      0.963   0.124   0.147  -0.165  bgcp   0.762    0.394    0.148   0.349                  intc   0.282    0.935            0.117                  fb     0.742    0.634    -0.171                                                '

the factional() function returns factanal object. estimated 2-factor model follows:

fmodel <- factanal(data, factors=2)

you can obtain estimated factor loadings using:

fmodel$loadings

to check out else estimated factional() function: see str(fmodel)


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