Package: BayesfMRI 0.8.0
BayesfMRI: Spatial Bayesian Methods for Task Functional MRI Studies
Performs a spatial Bayesian general linear model (GLM) for task functional magnetic resonance imaging (fMRI) data on the cortical surface. Additional models include group analysis and inference to detect thresholded areas of activation. Includes direct support for the 'CIFTI' neuroimaging file format. For more information see A. F. Mejia, Y. R. Yue, D. Bolin, F. Lindgren, M. A. Lindquist (2020) <doi:10.1080/01621459.2019.1611582> and D. Spencer, Y. R. Yue, D. Bolin, S. Ryan, A. F. Mejia (2022) <doi:10.1016/j.neuroimage.2022.118908>.
Authors:
BayesfMRI_0.8.0.tar.gz
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BayesfMRI.pdf |BayesfMRI.html✨
BayesfMRI/json (API)
NEWS
# Install 'BayesfMRI' in R: |
install.packages('BayesfMRI', repos = c('https://mandymejia.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mandymejia/bayesfmri/issues
Last updated 4 months agofrom:8250b37b00. Checks:OK: 6 NOTE: 3. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 24 2024 |
R-4.5-win-x86_64 | NOTE | Oct 24 2024 |
R-4.5-linux-x86_64 | NOTE | Oct 24 2024 |
R-4.4-win-x86_64 | OK | Oct 24 2024 |
R-4.4-mac-x86_64 | OK | Oct 24 2024 |
R-4.4-mac-aarch64 | OK | Oct 24 2024 |
R-4.3-win-x86_64 | NOTE | Oct 24 2024 |
R-4.3-mac-x86_64 | OK | Oct 24 2024 |
R-4.3-mac-aarch64 | OK | Oct 24 2024 |
Exports:activationsBayesGLMBayesGLM_groupBayesGLM2cderivfit_bayesglmHRF_calcHRF_mainHRF96id_activationsmake_designmake_maskmake_meshmultiGLMmultiGLM_funplot_designplot_design_imageplot_design_lineprevalencescale_BOLDvertex_areasvol2spde
Dependencies:abindbackportsbase64encbitopsbootbroombslibcachemcarcarDataciftiToolsclassclassIntclicodetoolscolorspacecowplotcpp11DBIDerivdigestdoBydotCall64dplyre1071evaluateexcursionsfansifarverfastmapfieldsfmesherfMRItoolsfontawesomeforeachFormulafsgenericsggplot2giftigluegtablehighrhtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelifecyclelme4magrittrmapsMASSMatrixMatrixModelsmatrixStatsmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellnlmenloptrnnetnumDerivoro.niftipbkrtestpillarpkgconfigproxypurrrquantregR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppEigenrglrlangrmarkdownRNiftis2sassscalessfspspamSparseMstringistringrsurvivaltibbletidyrtidyselecttinytexunitsutf8vctrsviridisLitewithrwkxfunxml2yaml