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


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")


TwoRegression 0.1.2


This is a resubmission of the initial version


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

TwoRegression 0.1.1


This is a resubmission of the initial version


  • 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


  • 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

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.1.2 by Paul R. Hibbing, 3 years ago

Report a bug at

Browse source code at

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