fmri_rlm: Fit a Robust Linear Model for fMRI Data Analysis

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

Fit a Robust Linear Model for fMRI Data Analysis

Description

This function fits a robust linear regression model for fMRI data analysis using the specified model formula, block structure, and dataset. The model can be fit using either a runwise or chunkwise data splitting strategy.

Usage

fmri_rlm(
  formula,
  block,
  baseline_model = NULL,
  dataset,
  durations = 0,
  drop_empty = TRUE,
  strategy = c("runwise", "chunkwise"),
  nchunks = 10,
  cor_struct = c("iid", "ar1", "ar2", "arp"),
  cor_iter = 1L,
  cor_global = FALSE,
  ar_p = NULL,
  ar1_exact_first = FALSE,
  robust_psi = c("huber", "bisquare"),
  robust_k_huber = 1.345,
  robust_c_tukey = 4.685,
  robust_max_iter = 2L,
  robust_scale_scope = c("run", "global"),
  ...
)

Arguments

formula	The model formula for experimental events.
block	The model formula for block structure.
baseline_model	(Optional) A baseline_model object. Default is NULL.
dataset	An fmri_dataset object containing the time-series data.
durations	A vector of event durations. Default is 0.
drop_empty	Logical. Whether to remove factor levels with zero size. Default is TRUE.
strategy	The data splitting strategy, either "runwise" or "chunkwise". Default is "runwise".
nchunks	Number of data chunks when strategy is "chunkwise". Default is 10.
cor_struct	Correlation structure: "iid", "ar1", "ar2", or "arp". Default is "iid".
cor_iter	Number of iterations for AR parameter estimation. Default is 1.
cor_global	Whether to use global AR parameters. Default is FALSE.
ar_p	Order of autoregressive model for "arp" structure. Default is NULL.
ar1_exact_first	Whether to use exact AR(1) for first iteration. Default is FALSE.
robust_psi	Robust psi function: "huber" or "bisquare". Default is "huber".
robust_k_huber	Tuning constant for Huber's psi. Default is 1.345.
robust_c_tukey	Tuning constant for Tukey's bisquare. Default is 4.685.
robust_max_iter	Maximum iterations for robust fitting. Default is 2.
robust_scale_scope	Scope for robust scale estimation: "run" or "global". Default is "run".
...	Additional arguments passed to fmri_lm

Value

A fitted robust linear regression model for fMRI data analysis.

Examples

etab <- data.frame(onset=c(1,30,15,25), fac=factor(c("A", "B", "A", "B")), run=c(1,1,2,2))
etab2 <- data.frame(onset=c(1,30,65,75), fac=factor(c("A", "B", "A", "B")), run=c(1,1,1,1))
mat <- matrix(rnorm(100*100), 100,100)
dset <- fmridataset::matrix_dataset(mat, TR=1, run_length=c(50,50),event_table=etab)
dset2 <- fmridataset::matrix_dataset(mat, TR=1, run_length=c(100),event_table=etab2)
lm.1 <- fmri_rlm(onset ~ hrf(fac), block= ~ run, dataset=dset)
lm.2 <- fmri_rlm(onset ~ hrf(fac), block= ~ run, dataset=dset2)

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