plotCP

internal

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

plotCP function

<dl><dt>fig</dt>
<dd>A partially-assembled figure</dd>
<dt>cutPoint</dt>
<dd>The threshold value to insert into the figure</dd>
<dt>x</dt>
<dd>numeric scalar giving x coordinate for label placement</dd>
<dt>y</dt>
<dd>numeric scalar giving y coordinate for label placement</dd></dl>

Arguments

Add a cut-point to a plot — plotCP

<dl>

<dt>fig</dt>
<dd>A partially-assembled figure</dd>


<dt>cutPoint</dt>
<dd>The threshold value to insert into the figure</dd>


<dt>x</dt>
<dd>numeric scalar giving x coordinate for label placement</dd>


<dt>y</dt>
<dd>numeric scalar giving y coordinate for label placement</dd>

</dl>

plotCP: Add a cut-point to a plot

Description

Usage

Arguments