sandwich_from_whitened_resid: GLS standard errors from whitened residuals

In fmriAR: Fast AR and ARMA Noise Whitening for Functional MRI (fMRI) Design and Data

GLS standard errors from whitened residuals

Description

GLS standard errors from whitened residuals

Usage

sandwich_from_whitened_resid(
  Xw,
  Yw,
  beta = NULL,
  type = c("iid", "hc0"),
  df_mode = c("rankX", "n-p"),
  runs = NULL
)

Arguments

Xw	Whitened design matrix.
Yw	Whitened data matrix (time x voxels).
beta	Optional coefficients (p x v); estimated if NULL.
type	Either "iid" (default) or "hc0" for a robust sandwich.
df_mode	Degrees-of-freedom mode: "rankX" (default) or "n-p".
runs	Optional run labels (reserved for future per-run scaling).

Value

List containing standard errors, innovation variances, and XtX inverse.

Examples

# Generate example whitened data
n_time <- 200
n_pred <- 3
n_voxels <- 50
Xw <- matrix(rnorm(n_time * n_pred), n_time, n_pred)
Yw <- matrix(rnorm(n_time * n_voxels), n_time, n_voxels)

# Compute standard errors
se_result <- sandwich_from_whitened_resid(Xw, Yw, type = "iid")

# Extract standard errors for first voxel
se_voxel1 <- se_result$se[, 1]

fmriAR documentation built on Jan. 26, 2026, 1:07 a.m.