.MixfMRIEnv

my.YlOrRd

my.YlGnBu

my.Reds

my.alpha.append

print.lmt.I

print.lmt.pv

internal

General Internal Functions

Utilizing model-based clustering (unsupervised)
for functional magnetic resonance imaging (fMRI) data.
The developed methods (Chen and Maitra (2023) <doi:10.1002/hbm.26425>)
include 2D and 3D clustering analyses
(for p-values with voxel locations) and
segmentation analyses (for p-values alone) for fMRI data where p-values
indicate significant level of activation responding to stimulate
of interesting. The analyses are mainly identifying active
voxel/signal associated with normal brain behaviors.
Analysis pipelines (R scripts) utilizing this package
(see examples in 'inst/workflow/') is also implemented with high
performance techniques.

Wei-Chen Chen

MixfMRI

Mixture fMRI Clustering Analysis

Ranjan Maitra

Dan Nettleton

Pierre Lafaye De Micheaux

Jonathan L Marchini

General Internal Functions function

Author

All General Internal Functions and Datasets — General Internal Functions

All General Internal Functions and Datasets

General Internal Functions: All General Internal Functions and Datasets

Description

Arguments

Author

References