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.'
| Version: |
0.1.1 |
| Depends: |
R (≥ 2.10) |
| Suggests: |
nnet, randomForest |
| Published: |
2026-04-01 |
| DOI: |
10.32614/CRAN.package.EE.Data (may not be active yet) |
| Author: |
Paul R. Hibbing [aut, cre],
Alexander H.K. Montoye [ctb],
John Staudenmayer [ctb],
Children's Mercy Kansas City [cph] |
| Maintainer: |
Paul R. Hibbing <paulhibbing at gmail.com> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
EE.Data results |
Documentation:
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