Computes the generalized means rotation for a given set of ENA points and predictor variables.
Usage
gmr(V, X)
Value
A numeric vector representing the rotation.
Arguments
V
A matrix containing ENA set points for projection.
X
A data frame containing all predictor variables, with the first column as the target variable.
Details
If X has only one column, a linear model is fit between V and the single predictor.
Otherwise, the main effect of the first predictor is extracted using get_x1_main_effect.
Singular value decomposition (SVD) is then performed, and the first right singular vector is used
to project the data. A linear model is fit to the projected data, and the coefficients are normalized
to produce the rotation vector.