The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Imputation for the missing count values in accelerometer data. The methodology includes both parametric and semi-parametric multiple imputations under the zero-inflated Poisson lognormal model. This package also provides multiple functions to pre-process the accelerometer data previous to the missing data imputation. These includes detecting wearing and non-wearing time, selecting valid days and subjects, and creating plots.
| Version: | 1.4 |
| Depends: | R (≥ 2.10), mice, pscl |
| Published: | 2018-04-06 |
| Author: | Jung Ae Lee |
| Maintainer: | Jung Ae Lee <jungaeleeb at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| In views: | MissingData |
| CRAN checks: | accelmissing results |
| Reference manual: | accelmissing.pdf |
| Package source: | accelmissing_1.4.tar.gz |
| Windows binaries: | r-devel: accelmissing_1.4.zip, r-release: accelmissing_1.4.zip, r-oldrel: accelmissing_1.4.zip |
| macOS binaries: | r-release (arm64): accelmissing_1.4.tgz, r-oldrel (arm64): accelmissing_1.4.tgz, r-release (x86_64): accelmissing_1.4.tgz, r-oldrel (x86_64): accelmissing_1.4.tgz |
| Old sources: | accelmissing archive |
Please use the canonical form https://CRAN.R-project.org/package=accelmissing to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.