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First release.
rsdcm() fits a robust, sparse group-level model to
subject-level DCM parameters: Student-t weighting of subjects for
robustness to outliers, a nonlocal product-moment (pMOM) spike-and-slab
prior for sparse selection of group effects, and ReML-estimated
between-subject variance components. It returns the group effects, their
posterior inclusion probabilities, the per-subject robustness weights,
and the learned spike/slab scales. See <arXiv:2609.06379>.rsdcm_fit() is a convenience wrapper that assembles the
inputs from a list of dcm_estimate() fits (the posterior
Ep/Cp restricted to a chosen parameter field)
and a between-subject design.narps_dcm: subject-level DCM summaries for 48 subjects
(with group/gender/age covariates), derived from the openly shared NARPS
dataset. It is the runnable real-data example for
rsdcm().message() and is silenceable,
matching the rest of the package.dcm_estimate(), dcm_nlsi_GN(),
dcm_int() ported from SPM25 with optimizations: propagator
caching in the bilinear integrator, identity-projection fast path in
dcm_diff(), diagonal fast paths in dcm_inv() /
dcm_logdet(). Roughly 20x faster end-to-end than a literal
port on representative DCMs.toy_dcm dataset (three regions, 482 scans) for
documentation, smoke-testing, and examples.introduction with a worked end-to-end
example.spm_dcm_peb:
dcm_peb_prepare() / dcm_peb_run(): prepare
and fit a second- or third-level PEB by variational Laplace.dcm_peb_of_pebs(): third-level PEB-of-PEBs over a
directory of subject PEBs, with a between-subject design.dcm_peb_design(): build the group-level design
matrix.dcm_peb_files() / dcm_peb_load(): locate
and load subject PEBs from .rds or MATLAB .mat
files (.mat needs the suggested R.matlab
package).dcm_peb_of_pebs() does not write to disk unless a
save_path is supplied.Ported SPM routines keep the dcm_ prefix (from
spm_), to avoid colliding with an installed SPM-derived
package and to make it obvious which functions come from here:
spm_dcm_estimate becomes dcm_estimate,
spm_nlsi_GN becomes dcm_nlsi_GN,
spm_int becomes dcm_int, and so on.
d array, is also supported).induced) variants are not yet implemented.
dcm_estimate() stops with an informative
error if any of these options is switched on, instead of
silently running the deterministic model. They are planned for a future
update.dcm_nlsi_GN() use
message() and can be silenced with
suppressMessages().dcm_estimate() does not write to disk by default. Pass
save = TRUE together with a file path to recover the SPM25
behaviour..spm_env global is replaced by a
package-internal environment whose mutable settings are exposed through
rsdcm_options().These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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