This package is considered a duplicate. The official version of this package is found at:https://nilotpalsanyal.r-universe.dev/BHMSMAfMRI

Package: BHMSMAfMRI 2.2

Nilotpal Sanyal

BHMSMAfMRI: Bayesian Hierarchical Multi-Subject Multiscale Analysis of Functional MRI (fMRI) Data

Package BHMSMAfMRI performs Bayesian hierarchical multi-subject multiscale analysis of fMRI data as described in Sanyal & Ferreira (2012) <doi:10.1016/j.neuroimage.2012.08.041>, or other multiscale data, using wavelet-based prior that borrows strength across subjects and provides posterior smoothed images of the effect sizes and samples from the posterior distribution.

Authors:Nilotpal Sanyal [aut, cre], Marco A.R. Ferreira [aut]

BHMSMAfMRI_2.2.tar.gz
BHMSMAfMRI_2.2.tar.gz(r-4.5-noble)BHMSMAfMRI_2.2.tar.gz(r-4.4-noble)
BHMSMAfMRI_2.2.tgz(r-4.4-emscripten)BHMSMAfMRI_2.2.tgz(r-4.3-emscripten)
BHMSMAfMRI.pdf |BHMSMAfMRI.html✨
BHMSMAfMRI/json (API)
NEWS

# Install 'BHMSMAfMRI' in R:

install.packages('BHMSMAfMRI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nilotpalsanyal/bhmsmafmri/issues

Pkgdown site:https://nilotpalsanyal.github.io

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

fmridata - A simulated fMRI data for 3 subjects

openblas cpp openmp

2.70 score 13 scripts 590 downloads 11 exports 8 dependencies

Last updated 7 months agofrom:4f006c3abe. Checks:OK: 1 WARNING: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 10 2024
R-4.5-linux-x86_64	WARNING	Dec 10 2024

Exports:BHMSMA glmcoef hyperparamest postglmcoef postgroupglmcoef postmixprob postsamples postwaveletcoef readfmridata substituteWaveletCoef waveletcoef

Dependencies:abind bitops MASS oro.nifti Rcpp RcppArmadillo RNifti wavethresh

BHMSMAfMRI User Guide

Nilotpal Sanyal

Rendered fromBHMSMAfMRIvignette.Rmdusingknitr::rmarkdownon Dec 10 2024.

Last update: 2022-10-02
Started: 2022-09-08

Citation

Readme and manuals

Help Manual

Help page	Topics
Bayesian Hierarchical Multi-Subject Multiscale Analysis (BHMSMA) of Functional MRI Data	BHMSMAfMRI
Bayesian hierarchical multi-subject multiscale analysis (BHMSMA) of functional MRI data or other multiscale data	BHMSMA
A simulated fMRI data for 3 subjects	fmridata
Fit GLM (general linear model) to the fMRI time-series of all voxels within a single 2D brain slice	glmcoef
Obtain estimates of the hyperparameters of the BHMSMA model	hyperparamest
Obtain posterior estimate of a 2D GLM coefficients map of a regressor	postglmcoef
Obtain posterior group estimate of a 2D GLM coefficients map of a regressor	postgroupglmcoef
Obtain estimates of the mixture probabilities defining the BHMSMA posterior wavelet coefficients distributions	postmixprob
Obtain samples from the posterior distribution of a 2D GLM coefficient map.	postsamples
Obtain posterior estimates of the BHMSMA wavelet coefficients	postwaveletcoef
Import fMRI data from various fMRI image files	readfmridata
Substitute 2D wavelet transform coefficients with user-given values	substituteWaveletCoef
Apply discrete wavelet transform (DWT) to a 2D GLM coefficient map of a regressor	waveletcoef