Extract a PCA/varimax loadings matrix
Examples
# \donttest{
set.seed(42)
theta = rdirichlet(50, 1, k = 3)
phi = rdirichlet(3, 0.1, k = 20)
corpus = draw_corpus(rep(50L, 50), theta, phi)
model = tmfast(corpus, n = 3)
loadings(model, k = 3)
#> [,1] [,2] [,3]
#> 2 -1.543494e+00 -1.519224e+00 -1.7283648049
#> 5 6.571852e-02 -8.608355e-02 -0.0143080031
#> 8 6.641125e+00 -3.139326e+00 5.3903500385
#> 11 -6.242402e-01 6.643635e+00 1.3328232630
#> 12 -4.667281e-02 1.561741e+00 0.3179324781
#> 17 -3.419079e+00 -1.534457e+00 -0.5708738590
#> 20 -1.171382e+00 -1.409401e+00 -3.6377716827
#> 1 6.910355e-01 -3.868725e-01 0.2261162142
#> 10 -6.086037e-01 -5.046854e-01 -1.2253537497
#> 4 6.937302e-02 3.988841e-01 0.1265788554
#> 16 -5.848587e-02 1.575057e-02 -0.0071641039
#> 18 -3.881459e-03 -3.016794e-05 -0.1320655380
#> 7 -5.553028e-03 -3.379211e-02 -0.0389026695
#> 15 1.612053e-06 -9.270514e-03 -0.0397392701
#> 6 1.413891e-02 3.131571e-03 0.0007428317
# }
v = stats::varimax(matrix(runif(20), nrow = 5))
loadings(v)
#>
#> Loadings:
#> [,1] [,2] [,3] [,4]
#> [1,] 0.441 0.984 0.563
#> [2,] 0.103 0.384 1.092
#> [3,] -0.118 1.131 0.179 0.830
#> [4,] 0.946 0.333
#> [5,] 0.157 0.907 -0.127 1.206
#>
#> [,1] [,2] [,3] [,4]
#> SS loadings 0.248 4.115 0.052 3.764
#> Proportion Var 0.050 0.823 0.010 0.753
#> Cumulative Var 0.050 0.873 0.883 1.636