fmri_rlm: fmri_rlm

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

fmri_rlm

Description

robust linear modeling of fmri data

Usage

fmri_rlm(
  formula,
  block,
  baseline_model = NULL,
  dataset,
  durations,
  drop_empty = TRUE,
  nchunks = 10,
  strategy = c("runwise", "slicewise", "all")
)

Arguments

formula	The model formula for experimental events.
block	The model formula for block structure.
baseline_model	(Optional) The baseline_model object. Default is NULL.
dataset	An object derived from fmri_dataset containing the time-series data.
durations	A vector of event durations.
drop_empty	Whether to remove factor levels with a size of zero. Default is TRUE.
nchunks	Number of data chunks when strategy is chunkwise. Default is 10.
strategy	The data splitting strategy, either "runwise" or "chunkwise". Default is "runwise".

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 <- matrix_dataset(mat, TR=1, run_length=c(50,50),event_table=etab)
dset2 <- 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 May 16, 2023, 10:56 a.m.