The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Lightweight utilities to estimate autoregressive (AR) and autoregressive moving average (ARMA) noise models from residuals and apply matched generalized least squares to whiten functional magnetic resonance imaging (fMRI) design and data matrices. The ARMA estimator follows a classic 1982 approach <doi:10.1093/biomet/69.1.81>, and a restricted AR family mirrors workflows described by Cox (2012) <doi:10.1016/j.neuroimage.2011.08.056>.
| Version: | 0.2.0 |
| Depends: | R (≥ 4.0) |
| Imports: | Rcpp, stats |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat (≥ 3.0.0), knitr, rmarkdown, abind, withr |
| Published: | 2025-11-03 |
| DOI: | 10.32614/CRAN.package.fmriAR |
| Author: | Bradley Buchsbaum [aut, cre] |
| Maintainer: | Bradley Buchsbaum <brad.buchsbaum at gmail.com> |
| License: | MIT + file LICENSE |
| URL: | https://bbuchsbaum.github.io/fmriAR/ |
| NeedsCompilation: | yes |
| SystemRequirements: | OpenMP (optional) |
| Materials: | README |
| CRAN checks: | fmriAR results |
| Reference manual: | fmriAR.html , fmriAR.pdf |
| Vignettes: |
Getting Started with fmriAR (source, R code) |
| Package source: | fmriAR_0.2.0.tar.gz |
| Windows binaries: | r-devel: fmriAR_0.2.0.zip, r-release: fmriAR_0.2.0.zip, r-oldrel: fmriAR_0.2.0.zip |
| macOS binaries: | r-release (arm64): fmriAR_0.2.0.tgz, r-oldrel (arm64): fmriAR_0.2.0.tgz, r-release (x86_64): fmriAR_0.2.0.tgz, r-oldrel (x86_64): fmriAR_0.2.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=fmriAR to link to this page.
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.
Health stats visible at Monitor.