TwoRegression: Process Data from Wearable Research Devices Using Two-Regression Algorithms

Application of two-regression algorithms for wearable research devices. It provides an easy way for users to read in device data files and apply an appropriate two-regression algorithm. More information is available from Hibbing PR, LaMunion SR, Kaplan AS, & Crouter SE (2017) <doi:10.1249/MSS.0000000000001532>.

Version: 0.1.2
Depends: R (≥ 2.10)
Imports: data.table (≥ 1.10.4), dplyr (≥ 0.5.0), seewave (≥ 2.0.5), magrittr (≥ 1.5), utils (≥ 3.2.4), stats (≥ 3.2.4)
Suggests: knitr, rmarkdown, testthat
Published: 2018-03-19
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

Downloads:

Reference manual: TwoRegression.pdf
Vignettes: The TwoRegression Package
Package source: TwoRegression_0.1.2.tar.gz
Windows binaries: r-prerel: TwoRegression_0.1.2.zip, r-release: TwoRegression_0.1.2.zip, r-oldrel: TwoRegression_0.1.2.zip
OS X binaries: r-prerel: TwoRegression_0.1.2.tgz, r-release: TwoRegression_0.1.2.tgz

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