A suite of tools useful to read, visualize and export bivariate motion energy time-series. Lagged synchrony between subjects can be analyzed through windowed cross-correlation. Surrogate data generation allows an estimation of pseudosynchrony that helps to estimate the effect size of the observed synchronization. Kleinbub, J. R., & Ramseyer, F. T. (2020). rMEA: An R package to assess nonverbal synchronization in motion energy analysis time-series. Psychotherapy research, 1-14. <doi:10.1080/10503307.2020.1844334>.
Version: | 1.2.2 |
Depends: | R (≥ 4.0.0) |
Imports: | grDevices, graphics, methods, stats, utils |
Published: | 2022-02-17 |
DOI: | 10.32614/CRAN.package.rMEA |
Author: | Johann R. Kleinbub, Fabian Ramseyer |
Maintainer: | Johann R. Kleinbub <johann.kleinbub at gmail.com> |
BugReports: | https://github.com/kleinbub/rMEA/issues |
License: | GPL-3 |
URL: | https://github.com/kleinbub/rMEA https://psync.ch |
NeedsCompilation: | no |
Citation: | rMEA citation info |
Materials: | README NEWS |
CRAN checks: | rMEA results |
Reference manual: | rMEA.pdf |
Package source: | rMEA_1.2.2.tar.gz |
Windows binaries: | r-devel: rMEA_1.2.2.zip, r-release: rMEA_1.2.2.zip, r-oldrel: rMEA_1.2.2.zip |
macOS binaries: | r-release (arm64): rMEA_1.2.2.tgz, r-oldrel (arm64): rMEA_1.2.2.tgz, r-release (x86_64): rMEA_1.2.2.tgz, r-oldrel (x86_64): rMEA_1.2.2.tgz |
Old sources: | rMEA archive |
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