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.

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

Downloads:

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
OS X binaries: r-release: permutes_1.0.tgz, r-oldrel: permutes_1.0.tgz
Old sources: permutes archive

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