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>
License: GPL-3 | file LICENSE
NeedsCompilation: no
Citation: TwoRegression citation info
Materials: README NEWS
CRAN checks: TwoRegression results


Reference manual: TwoRegression.pdf
Vignettes: The TwoRegression Package


Package source: TwoRegression_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): TwoRegression_1.0.0.tgz, r-oldrel (arm64): TwoRegression_1.0.0.tgz, r-release (x86_64): TwoRegression_1.0.0.tgz, r-oldrel (x86_64): TwoRegression_1.0.0.tgz
Old sources: TwoRegression archive


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