fmri_lm_fit: Fit an fMRI Linear Regression Model with a Specified Fitting...

In bbuchsbaum/fmrireg: R package for the anlysis of fmri data

Fit an fMRI Linear Regression Model with a Specified Fitting Strategy

Description

This function fits an fMRI linear regression model using the specified fmri_model object, dataset, and data splitting strategy (either "runwise" or "chunkwise"). It is primarily an internal function used by the fmri_lm function.

Usage

fmri_lm_fit(
  fmrimod,
  dataset,
  strategy = c("runwise", "chunkwise"),
  cfg,
  nchunks = 10,
  use_fast_path = FALSE,
  progress = FALSE,
  extra_nuisance = NULL,
  keep_extra_nuisance_in_model = FALSE,
  parallel_voxels = FALSE,
  ...
)

Arguments

fmrimod	An fmri_model object.
dataset	An fmri_dataset object containing the time-series data.
strategy	The data splitting strategy, either "runwise" or "chunkwise". Default is "runwise".
cfg	An fmri_lm_config object containing all fitting options. See fmri_lm_control.
nchunks	Number of data chunks when strategy is "chunkwise". Default is 10.
use_fast_path	Logical. If TRUE, use matrix-based computation for speed. Default is FALSE.
progress	Logical. Whether to display a progress bar during model fitting. Default is FALSE.
extra_nuisance	Optional matrix or formula specifying additional nuisance regressors.
keep_extra_nuisance_in_model	Logical. Whether to keep extra nuisance regressors in the final model. Default is FALSE.
parallel_voxels	Logical. If TRUE, voxelwise AR processing within runs is parallelised using future.apply. Default is FALSE.
...	Additional arguments.

Value

A fitted fMRI linear regression model with the specified fitting strategy.

See Also

fmri_lm, fmri_model, fmri_dataset

bbuchsbaum/fmrireg documentation built on June 10, 2025, 8:18 p.m.