TwoRegression: Develop and Apply Two-Regression Algorithms
Facilitates development and application of two-regression
algorithms for research-grade wearable devices. It provides an easy
way for users to access previously-developed algorithms, and also to
develop their own. Initial motivation came from Hibbing PR, LaMunion SR,
Kaplan AS, & Crouter SE (2018) <doi:10.1249/MSS.0000000000001532>.
However, other algorithms are now supported. Please see the associated
references in the package documentation for full details of the algorithms
that are supported.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
dplyr (≥ 0.5.0), ggplot2 (≥ 2.2.0), magrittr (≥ 1.5), gridExtra (≥ 2.3), PAutilities (≥ 1.1.0), pROC (≥ 1.16.0), RcppRoll, stats, rlang, lubridate, tidyr |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2022-09-05 |
| Author: |
Paul R. Hibbing [aut, cre],
Vincent T. van Hees [ctb] |
| Maintainer: |
Paul R. Hibbing <paulhibbing at gmail.com> |
| BugReports: |
https://github.com/paulhibbing/TwoRegression/issues |
| License: |
GPL-3 | file LICENSE |
| URL: |
https://github.com/paulhibbing/TwoRegression |
| NeedsCompilation: |
no |
| Citation: |
TwoRegression citation info |
| Materials: |
README NEWS |
| CRAN checks: |
TwoRegression results |
Documentation:
Downloads:
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