raw_for_cv

A partially-processed primary accelerometer dataset ready to calculate the
coefficient of variation per 10-s

datasets

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.

Paul Hibbins

TwoRegression

Develop and Apply Two-Regression Algorithms

raw_for_cv function

A data frame with 299 rows and 2 variables:<dl>
 <dt>Block</dt>
<dd>A vestigial variable synonymous with row number</dd> <dt>ENMO</dt>
<dd>Euclidian Norm Minus One, in milli-g</dd>
</dl>

Format

Primary accelerometer data to calculate coefficient of variation per 10-s — raw_for_cv

A data frame with 299 rows and 2 variables:<dl>
 <dt>Block</dt>
<dd>A vestigial variable synonymous with row number</dd>

 <dt>ENMO</dt>
<dd>Euclidian Norm Minus One, in milli-g</dd>


</dl>

raw_for_cv: Primary accelerometer data to calculate coefficient of variation per 10-s

Description

Usage

Arguments

Format