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.
| Version: | 1.0 |
| Depends: | R (≥ 2.10) |
| Imports: | ggplot2, lmPerm, plyr, viridis |
| Suggests: | doParallel, dplyr, tidyr, knitr, rmarkdown |
| Published: | 2019-07-21 |
| Author: | Cesko C. Voeten [aut, cre] |
| Maintainer: | Cesko C. Voeten <cvoeten at gmail.com> |
| BugReports: | https://github.com/cvoeten/permutes/issues |
| License: | FreeBSD |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | permutes results |
| Reference manual: | permutes.pdf |
| Vignettes: |
Analyzing time series data using the ‘permutes’ package |
| Package source: | permutes_1.0.tar.gz |
| Windows binaries: | r-devel: permutes_1.0.zip, r-release: permutes_1.0.zip, r-oldrel: permutes_1.0.zip |
| macOS binaries: | r-release: permutes_1.0.tgz, r-oldrel: permutes_1.0.tgz |
| Old sources: | permutes archive |
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