rsDCM: Robust and Sparse Dynamic Causal Modelling for Functional MRI
Fits robust and sparse group-level Dynamic Causal Models (DCMs)
for functional magnetic resonance imaging data. The group method combines
a Student-t likelihood with a Gaussian-spike and nonlocal product-moment
slab prior, propagates first-level posterior covariance through block
pre-whitening, fits empirical-Bayes modes by multistart generalized
expectation-maximization with conditional maximization, and integrates
posterior inclusion probabilities by parallel-tempering Monte Carlo
(<doi:10.48550/arXiv.2609.06379>). The package also provides an R port of
deterministic single-state DCM and Parametric Empirical Bayes routines
from 'SPM25' (version 25.01.02), based on Friston et al. (2003)
<doi:10.1016/S1053-8119(03)00202-7>.
| Version: |
0.2.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
Matrix, Rcpp, expm, MASS, methods, stats, utils |
| LinkingTo: |
Rcpp |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown, R.matlab, withr |
| Published: |
2026-11-14 |
| DOI: |
10.32614/CRAN.package.rsDCM |
| Author: |
Godfred Arhin [aut, cre, trl],
Nilotpal Sanyal [aut],
SPM25 Authors [ctb, cph] (Original MATLAB SPM25 (v25.01.02)
implementation; see LICENSE.note) |
| Maintainer: |
Godfred Arhin <arhin0122 at gmail.com> |
| BugReports: |
https://github.com/Kay202/rsDCM/issues |
| License: |
GPL-2 |
| URL: |
https://kay202.github.io/rsDCM/ |
| NeedsCompilation: |
yes |
| Citation: |
rsDCM citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
rsDCM results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=rsDCM
to link to this page.