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Several functions can be used to analyze neuroimaging data using multivariate methods based on the 'msma' package. The functions used in the book entitled "Multivariate Analysis for Neuroimaging Data" (2021, ISBN-13: 978-0367255329) are contained.
| Version: | 2.0 |
| Depends: | R (≥ 3.5), msma |
| Imports: | oro.nifti, oro.dicom, imager, caret |
| Suggests: | knitr, rmarkdown |
| Published: | 2023-09-12 |
| DOI: | 10.32614/CRAN.package.mand |
| Author: | Atsushi Kawaguchi [aut, cre] |
| Maintainer: | Atsushi Kawaguchi <kawa_a24 at yahoo.co.jp> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | mand citation info |
| CRAN checks: | mand results |
| Reference manual: | mand.pdf |
| Vignettes: |
Overview 1 Introduction 2 Brain Imaging Data 3 Common Statistical Approach 4.1 Matrix Decomposition 4.2 Prediction Model 5 Multi-block Approach |
| Package source: | mand_2.0.tar.gz |
| Windows binaries: | r-devel: mand_2.0.zip, r-release: mand_2.0.zip, r-oldrel: mand_2.0.zip |
| macOS binaries: | r-release (arm64): mand_2.0.tgz, r-oldrel (arm64): mand_2.0.tgz, r-release (x86_64): mand_2.0.tgz, r-oldrel (x86_64): mand_2.0.tgz |
| Old sources: | mand archive |
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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.