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.
Вопрос
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
Решение
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.