Project Out Confound Variables — project

Computes the orthogonal projection matrix Q = I - X(X'X)^(-1)X' that projects out the space spanned by confound regressors X. This is useful for advanced users who want to cache and reuse projection matrices.

Usage

project_confounds(X)

Arguments

X: Confound design matrix (n x p) where n is number of timepoints and p is number of confound regressors

Value

Projection matrix Q (n x n) that projects out the column space of X

Details

This function uses QR decomposition for numerical stability instead of computing the Moore-Penrose pseudoinverse directly. The resulting matrix Q can be applied to data to remove the influence of confound regressors.

Examples

if (FALSE) { # \dontrun{
n <- 100
X_confounds <- cbind(1, 1:n)

Q <- project_confounds(X_confounds)

Y_clean <- Q %*% Y_raw
} # }