permutes: Permutation Tests for Time Series Data
Helps you determine the analysis window to use when analyzing densely-sampled
time-series data, such as EEG data, using permutation testing (Maris & Oostenveld, 2007)
<doi:10.1016/j.jneumeth.2007.03.024>. These permutation tests can help identify the timepoints
where significance of an effect begins and ends, and the results can be plotted in various
types of heatmap for reporting. Mixed-effects models are supported using an implementation of
the approach by Lee & Braun (2012) <doi:10.1111/j.1541-0420.2011.01675.x>.
| Version: |
2.8 |
| Depends: |
R (≥ 2.10) |
| Imports: |
plyr, stats, utils |
| Suggests: |
buildmer (≥ 2.3), car, doParallel, ggplot2, glmmTMB, knitr, lme4, lmPerm, permuco, rmarkdown, viridis |
| Published: |
2023-09-28 |
| DOI: |
10.32614/CRAN.package.permutes |
| Author: |
Cesko C. Voeten [aut, cre] |
| Maintainer: |
Cesko C. Voeten <cvoeten at gmail.com> |
| BugReports: |
https://gitlab.com/cvoeten/permutes/-/issues |
| License: |
FreeBSD |
| NeedsCompilation: |
no |
| CRAN checks: |
permutes results |
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