Installation
About
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.
| Citation | rMEA citation info |
| github.com/kleinbub/rMEA https://psync.ch | |
| github.com/kleinbub/rMEA https://psync.ch | |
| Bug report | File report |
Key Metrics
Downloads
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| Last 7 days | 173 -26% |
| Last 30 days | 697 -44% |
| Last 90 days | 2.390 +9% |
| Last 365 days | 8.499 +36% |
Maintainer
| Maintainer | Johann R. Kleinbub |
Depends
| R | ≥ 4.0.0 |
Imports
| grDevices | |
| graphics | |
| methods | |
| stats | |
| utils |