accelmissing: Missing Value Imputation for Accelerometer Data

We present a statistical method for imputing missing values in accelerometer data. The methodology includes both parametric and semi-parametric multiple imputation under the zero-inflated Poisson lognormal model. It also offers several functions to preprocess accelerometer data before imputation. These include detecting wear and non-wear time, selecting valid days and subjects, and generating plots.

Version:	2.2
Depends:	R (≥ 3.5.0), mice, pscl
Published:	2025-05-30
Author:	Jung Ae Lee [aut, cre]
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

Documentation:

Reference manual:

accelmissing.html , accelmissing.pdf

Downloads:

Package source:	accelmissing_2.2.tar.gz
Windows binaries:	r-devel: accelmissing_2.2.zip, r-release: accelmissing_2.2.zip, r-oldrel: accelmissing_2.2.zip
macOS binaries:	r-release (arm64): accelmissing_2.2.tgz, r-oldrel (arm64): accelmissing_2.2.tgz, r-release (x86_64): accelmissing_2.2.tgz, r-oldrel (x86_64): accelmissing_2.2.tgz
Old sources:	accelmissing archive

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