rMEA: Synchrony in Motion Energy Analysis (MEA) Time-Series

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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