Package: fmrilss 0.1.0
fmrilss: Least Squares Separate (LSS) Analysis for fMRI Data
Implements efficient least squares separate (LSS) analysis for functional magnetic resonance imaging (fMRI) data. LSS is used to estimate trial-by-trial activation patterns in event-related fMRI designs. The package provides both R and C++ implementations for computational efficiency.
Authors:
fmrilss_0.1.0.tar.gz
fmrilss_0.1.0.zip(r-4.7)fmrilss_0.1.0.zip(r-4.6)fmrilss_0.1.0.zip(r-4.5)
fmrilss_0.1.0.tgz(r-4.6-x86_64)fmrilss_0.1.0.tgz(r-4.6-arm64)fmrilss_0.1.0.tgz(r-4.5-x86_64)fmrilss_0.1.0.tgz(r-4.5-arm64)
fmrilss_0.1.0.tar.gz(r-4.7-arm64)fmrilss_0.1.0.tar.gz(r-4.7-x86_64)fmrilss_0.1.0.tar.gz(r-4.6-arm64)fmrilss_0.1.0.tar.gz(r-4.6-x86_64)
fmrilss_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fmrilss/json (API)
NEWS
| # Install 'fmrilss' in R: |
| install.packages('fmrilss', repos = c('https://bbuchsbaum.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bbuchsbaum/fmrilss/issues
Pkgdown/docs site:https://bbuchsbaum.github.io
Last updated from:e8d305562b. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 283 | ||
| linux-devel-x86_64 | OK | 271 | ||
| source / vignettes | OK | 346 | ||
| linux-release-arm64 | OK | 251 | ||
| linux-release-x86_64 | OK | 270 | ||
| macos-release-arm64 | OK | 183 | ||
| macos-release-x86_64 | OK | 327 | ||
| macos-oldrel-arm64 | OK | 138 | ||
| macos-oldrel-x86_64 | OK | 363 | ||
| windows-devel | OK | 311 | ||
| windows-release | OK | 319 | ||
| windows-oldrel | OK | 306 | ||
| wasm-release | OK | 176 |
Exports:benchmark_mixed_solvecalculate_recovery_metricscompare_hrf_recoverycreate_lwu_gridestimate_voxel_hrffit_oasis_gridgenerate_lwu_datagenerate_rapid_designget_data_matrixitem_build_designitem_compute_uitem_cvitem_fititem_from_lsaitem_predictitem_slice_foldlsalsslss_beta_cpplss_cpp_optimizedlss_designlss_naivelss_naive_fitlss_optimizedlss_optimized_fitlss_sbhmlss_sbhm_designlss_with_hrfmixed_precomputemixed_solvemixed_solve_cppmixed_solve_optimizedoasis_optionsplot_hrf_comparisonprewhiten_optionsproject_confoundsproject_confounds_cppsbhm_buildsbhm_hrfsbhm_matchsbhm_prepasssbhm_projectstglmnet_options
Dependencies:assertthatBHbigmemorybigmemory.sricachemclicodetoolscpp11farverfastmapfmriARfmrihrfforeachggplot2glmnetgluegtableisobanditeratorsjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmemoisenumDerivpracmapurrrR6RColorBrewerRcppRcppArmadilloRcppEigenrlangroptimS7scalesshapesurvivaluuidvctrsviridisLitewithr
Getting started with fmrilss
Rendered fromfmrilss.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2026-04-11
Started: 2026-02-06
OASIS Theory: Algebra and Implementation Details
Rendered fromoasis_theory.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2026-04-11
Started: 2025-09-15
Shared-Basis HRF Matching (SBHM): Efficient Voxel-Specific HRF Estimation
Rendered fromsbhm.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2026-04-11
Started: 2025-10-31
The OASIS Method: Optimized Analytic Single-pass Inverse Solution
Rendered fromoasis_method.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2026-04-11
Started: 2025-08-23
Using fmridesign with fmrilss
Rendered fromlss_with_fmridesign.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2026-04-11
Started: 2025-11-06
Voxel-wise HRF Modeling with fmrilss
Rendered fromvoxel-wise-hrf.Rmdusingknitr::rmarkdownon Jun 04 2026.Last update: 2026-04-11
Started: 2025-06-16
