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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
2.2 |
rolling linux/jammy R-4.5 | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
rolling linux/noble R-4.5 | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
rolling source/ R- | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
latest linux/jammy R-4.5 | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
latest linux/noble R-4.5 | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
latest source/ R- | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
2026-04-26 source/ R- | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
2026-04-23 source/ R- | accelmissing_2.2.tar.gz |
4.6 MiB |
2.2 |
2026-04-09 windows/windows R-4.5 | accelmissing_2.2.zip |
4.6 MiB |
1.4 |
2025-04-20 source/ R- | accelmissing_1.4.tar.gz |
4.6 MiB |