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) .


Build Status

Overview

TwoRegression is a package designed to simplify the use of two-regression algorithms. The vignette ("TwoRegression") contains more specific information. To install the package and view the vignette, use:

# vignette("TwoRegression")

News

TwoRegression 0.1.2

Summary

This is a resubmission of the initial version

Changes

  • For internal functions, corrected examples by prepending with TwoRegression:::, or by removing the example(s)

TwoRegression 0.1.1

Summary

This is a resubmission of the initial version

Changes

  • Listed Vincent van Hees as a contributor in the DESCRIPTION file
  • Added a reference to Hibbing et al. (2017) <10.1249/MSS.0000000000001532> in the DESCRIPTION file
  • Added executable examples to function documentation
  • Incremented version from 0.1.0 to 0.1.1, for clarity

TwoRegression 0.1.0

Summary

  • This is the initial version of TwoRegression
  • The two-regression algorithms of Hibbing et al. (2017, Med Sci Sports Exerc) are currently supported

Reference manual

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install.packages("TwoRegression")

0.1.2 by Paul R. Hibbing, a year ago


https://github.com/paulhibbing/TwoRegression


Report a bug at https://github.com/paulhibbing/TwoRegression/issues


Browse source code at https://github.com/cran/TwoRegression


Authors: Paul R. Hibbing [aut, cre] , Vincent T. van Hees [ctb]


Documentation:   PDF Manual  


GPL-3 | file LICENSE license


Imports data.table, dplyr, seewave, magrittr, utils, stats

Suggests knitr, rmarkdown, testthat


See at CRAN