Penalized Multi-Band Learning algorithm can be effectively implemented for circadian rhythm analysis and daily activity pattern characterization using actigraphy (continuously measured objective physical activity data). Functions for interactive visualization of actigraph data are also included. Method reference: Li, X., Kane, M., Zhang, Y., Sun, W., Song, Y., Dong, S., Lin, Q., Zhu, Q., Jiang, F., Zhao, H. (2019) A Novel Penalized Multi-band Learning Approach Characterizes the Consolidation of Sleep-Wake Circadian Rhythms During Early Childhood Development.
| Version: | 1.2 |
| Depends: | R (≥ 3.4.0) |
| Imports: | tidyr, rbokeh, dplyr, tibble |
| Suggests: | knitr, rmarkdown |
| Published: | 2020-02-11 |
| Author: | Xinyue Li [aut, cre], Michael Kane [aut] |
| Maintainer: | Xinyue Li <xinyue.li at yale.edu> |
| BugReports: | https://github.com/xinyue-L/PML/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://github.com/xinyue-L/PML |
| NeedsCompilation: | no |
| CRAN checks: | PML results |
| Reference manual: | PML.pdf |
| Vignettes: |
Package PML User Manual |
| Package source: | PML_1.2.tar.gz |
| Windows binaries: | r-devel: PML_1.2.zip, r-release: PML_1.2.zip, r-oldrel: PML_1.2.zip |
| macOS binaries: | r-release: PML_1.2.tgz, r-oldrel: PML_1.2.tgz |
| Old sources: | PML archive |
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