cannot obtain all dimensions with FactoMiner

Question

I am performing a PCA analysis with FactoMiner with 7 variables, and having these results with 7 dimensions to account for 100% of variation: Eigenvalues

                       Dim.1   Dim.2   Dim.3   Dim.4   Dim.5   Dim.6   Dim.7
Variance               2.482   1.445   1.223   0.944   0.619   0.193   0.095
% of var.             35.453  20.636  17.471  13.484   8.838   2.754   1.364
Cumulative % of var.  35.453  56.090  73.561  87.045  95.882  98.636 100.000

However, when I call summary(pca_pa, ncp=7) it does not give me results of the contribution of each variable upto 7 dimensions but only maximum 5 dimensions. For example, this is what I get for contributions of each variable for1st three dimensions:

Variables
                   Dim.1    ctr   cos2    Dim.2    ctr   cos2    Dim.3    ctr
b_0             | -0.007  0.002  0.000 |  0.133  1.229  0.018 |  0.857 60.111
v_X             |  0.308  3.815  0.095 |  0.034  0.078  0.001 | -0.625 31.897
W_M             | -0.737 21.884  0.543 |  0.561 21.761  0.314 | -0.204  3.407
v_Y             | -0.016  0.011  0.000 | -0.858 50.958  0.736 |  0.116  1.092
v_F             |  0.940 35.586  0.883 | -0.004  0.001  0.000 | -0.058  0.278
v_P             |  0.922 34.228  0.849 |  0.220  3.364  0.049 |  0.043  0.150
v_L             |  0.333  4.474  0.111 |  0.571 22.609  0.327 |  0.194  3.066

I would like to have this table for all 7 dimensions. Would you please help me? Thanks!

Phuong

Answer 1

Maybe this could work for you:

summary(pca_pa, ncp=7, nbelements=Inf)

The nbelements option is the number of written columns. It is 10 by default.