Package: EE.Data
Type: Package
Title: Objects for Predicting Energy Expenditure
Version: 0.1.1
Authors@R: c(
      person(c("Paul", "R."), "Hibbing", email = "paulhibbing@gmail.com", role = c("aut","cre")),
      person(c("Alexander", "H.K."), "Montoye", email = "alexander.montoye@montcalm.edu", role = "ctb"),
      person("John", "Staudenmayer", email = "jstauden@math.umass.edu", role = "ctb"),
      person("Children's Mercy Kansas City", role = "cph")
    )
Description: This is a data-only package containing model objects that predict
    human energy expenditure from wearable sensor data. Supported methods include
    the neural networks of Montoye et al. (2017) <doi:10.1080/1091367X.2017.1337638>
    and the models of Staudenmayer et al. (2015) <doi:10.1152/japplphysiol.00026.2015>,
    one a linear model and the other a random forest. The package is intended as
    a spoke for the hub-package 'accelEE', which brings together the above methods
    and others from packages such as 'Sojourn' and 'TwoRegression.'
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Suggests: nnet, randomForest
Depends: R (>= 2.10)
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-03-28 11:20:13 UTC; phibbing
Author: Paul R. Hibbing [aut, cre],
  Alexander H.K. Montoye [ctb],
  John Staudenmayer [ctb],
  Children's Mercy Kansas City [cph]
Maintainer: Paul R. Hibbing <paulhibbing@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-01 08:50:16 UTC
Built: R 4.6.0; ; 2026-05-30 01:57:51 UTC; windows
