neuroim2 (version 0.8.5)

prepare_confounds: Prepare weighted nuisance projectors for each run

Description

Converts per-run confound matrices and time weights into orthonormal projectors that can be consumed directly by the C++ graph builder. Each run produces \(Q_k\) (columns spanning the weighted confound space) and \(\sqrt{w_k}\) (per-time-point square-root weights). Supplying a NULL confound matrix yields a zero-column projector, enabling pure time-weighting without regression.

Usage

prepare_confounds(
  confounds,
  time_weights = NULL,
  run_lengths,
  include_intercept = TRUE,
  center_cols = TRUE,
  scale_cols = FALSE
)

Value

A list with elements Q_list (list of matrices) and

sqrtw_list (list of numeric vectors). Each entry has the same length as run_lengths.

Arguments

confounds

List of matrices (\(T_k \times p_k\)), or a single matrix reused for all runs. Each row corresponds to a time point.

time_weights

Optional list of numeric vectors (length \(T_k\)) or a single vector reused for every run. If NULL, unit weights are used.

run_lengths

Integer vector with the number of time points per run. Required when any run has both confounds=NULL and time_weights=NULL.

include_intercept

Logical; prepend a column of ones before QR (default TRUE).

center_cols

Logical; center each confound column before weighting (default TRUE).

scale_cols

Logical; scale columns to unit variance before weighting (default FALSE).