ARI {ARIbrain} | R Documentation |
Valid Circular Inference (ARI) for Brain Imaging
Description
Valid Circular Inference (ARI) for Brain Imaging
Usage
ARI(Pmap, clusters, mask = NULL, alpha = 0.05, Statmap = function(ix)
-qnorm(Pmap[ix]), summary_stat = c("max", "center-of-mass"),
silent = FALSE)
Arguments
Pmap |
3D array of p-values or a (character) nifti file name. |
clusters |
3D array of cluster ids (0 when voxel does not belong to any cluster) or a (character) nifti file name. |
mask |
3D array of locicals (i.e. |
alpha |
Significance level. |
Statmap |
Statistics (usually t-values) on which the summaries are based. Can be either
a 3D array, a (character) nifti file name or a function with argument |
summary_stat |
Choose among |
silent |
|
Value
A matrix
reporting Size, FalseNull, TrueNull, ActiveProp and other statistics for each cluster.
Examples
pvalue_name <- system.file("extdata", "pvalue.nii.gz", package="ARIbrain")
cluster_name <- system.file("extdata", "cluster_th_3.2.nii.gz", package="ARIbrain")
zstat_name <- system.file("extdata", "zstat.nii.gz", package="ARIbrain")
mask_name <- system.file("extdata", "mask.nii.gz", package="ARIbrain")
print(mask_name)
print(pvalue_name)
print(cluster_name)
print(zstat_name)
ARI(Pmap = pvalue_name, clusters= cluster_name,
mask=mask_name, Statmap = zstat_name)