EE.Data
Objects for Predicting Energy Expenditure
This is a data-only package containing model objects that predict human energy expenditure from wearable sensor data. Supported methods include the neural networks of Montoye et al. (2017) <doi:10.1080/1091367X.2017.1337638> and the models of Staudenmayer et al. (2015) <doi:10.1152/japplphysiol.00026.2015>, one a linear model and the other a random forest. The package is intended as a spoke for the hub-package 'accelEE', which brings together the above methods and others from packages such as 'Sojourn' and 'TwoRegression.'
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling source/ R- | EE.Data_0.1.1.tar.gz |
7.1 MiB |
0.1.1 |
latest source/ R- | EE.Data_0.1.1.tar.gz |
7.1 MiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | EE.Data_0.1.1.zip |
7.0 MiB |