local_factors {l1rotation} | R Documentation |
Check whether local factors are present and find the rotation of the loading matrix with the smallest l1-norm.
Description
local_factors
tests whether local factors are present and returns both the Principal Component estimate of the loadings and the rotation of the loadings with the smallest l1-norm. It also produces graphical illustrations of the results.
Usage
local_factors(X, r, parallel = FALSE, n_cores = NULL)
Arguments
X |
A (usually standardized) t by n matrix of observations. |
r |
An integer denoting the number of factors in X. |
parallel |
A logical denoting whether the algorithm should be run in parallel. |
n_cores |
An integer denoting how many cores should be used, if parallel == TRUE. |
Value
Returns a list with the following components:
-
has_local_factors
A logical equal toTRUE
if local factors are present. -
initial_loadings
Principal component estimate of the loading matrix. -
rotated_loadings
Matrix that is the rotation of the loading matrix that produces the smallest l1-norm. -
rotation_diagnostics
A list containing 3 components:-
R
Rotation matrix that when used to rotateinitial_loadings
produces the smallest l1-norm. -
l1_norm
Vector of lengthr
containing the value of the l1 norm each solution generates. -
sol_frequency
Vector of lengthr
containing the frequency in the initial grid of each solution.
-
-
pc_plot
Tile plot of the Principal Component estimate of the loading matrix. -
rotated_plot
Tile plot of the l1-rotation of the loading matrix estimate. -
small_loadings_plot
Plot of the number of small loadings for each column of the l1-rotation of the loading matrix estimate.
Examples
# Minimal example with 2 factors, where X is a 224 by 207 matrix
lf <- local_factors(X = example_data, r = 2)
# Visualize Principal Component estimate of the loadings
lf$pc_plot
# Visualize l1-rotation loadings
lf$pc_rotated_plot