count_data

A small amount of 10-s epoch activity counts for code examples

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

count_data function

A data frame with 30 rows and 5 variables:<dl>
 <dt>time</dt>
<dd>POSIX. The timestamp</dd> <dt>Axis1</dt>
<dd>numeric. The vertical axis activity counts</dd> <dt>Axis2</dt>
<dd>numeric. The horizontal axis</dd> <dt>Axis3</dt>
<dd>numeric. The lateral axis</dd> <dt>Vector.Magnitude</dt>
<dd>numeric. The vector magnitude of all three axes</dd>
</dl>

Format

Activity count data for demonstrating prior two-regression models — count_data

A data frame with 30 rows and 5 variables:<dl>
 <dt>time</dt>
<dd>POSIX. The timestamp</dd>

 <dt>Axis1</dt>
<dd>numeric. The vertical axis activity counts</dd>

 <dt>Axis2</dt>
<dd>numeric. The horizontal axis</dd>

 <dt>Axis3</dt>
<dd>numeric. The lateral axis</dd>

 <dt>Vector.Magnitude</dt>
<dd>numeric. The vector magnitude of all three axes</dd>


</dl>

count_data: Activity count data for demonstrating prior two-regression models

Description

Usage

Arguments

Format