decreasing_smoother

decreasingSmoother

The regressor passed on to the <code>formula</code> argument of <code><a rd-options="scam" href="/link/scam?package=trackeR&version=1.5.2&to=scam" data-mini-rdoc="scam::scam">scam</a></code>.

The response passed on to the <code>formula</code> argument of <code><a rd-options="scam" href="/link/scam?package=trackeR&version=1.5.2&to=scam" data-mini-rdoc="scam::scam">scam</a></code>.

If <code>NULL</code>, the default, <code>x</code> is used for prediction. Otherwise,
prediction is done over the range of <code>x</code> with <code>len</code> equidistant points.

A vector of smoothing parameters passed on to <code><a rd-options="scam" href="/link/scam?package=trackeR&version=1.5.2&to=scam" data-mini-rdoc="scam::scam">scam</a></code>.

This smoother ensures a positive response that is a monotone decreasing function of x.

Provides infrastructure for handling running, cycling and swimming data from GPS-enabled tracking devices within R. The package provides methods to extract, clean and organise workout and competition data into session-based and unit-aware data objects of class 'trackeRdata' (S3 class). The information can then be visualised, summarised, and analysed through flexible and extensible methods. Frick and Kosmidis (2017) <doi: 10.18637/jss.v082.i07>, which is updated and maintained as one of the vignettes, provides detailed descriptions of the package and its methods, and real-data demonstrations of the package functionality.

Ioannis Kosmidis

trackeR

Infrastructure for Running, Cycling and Swimming Data from
GPS-Enabled Tracking Devices

Hannah Frick

Robin Hornak

decreasing_smoother function

<dl><dt>x</dt>
<dd>The regressor passed on to the <code>formula</code> argument of <code>scam</code>.</dd>
<dt>y</dt>
<dd>The response passed on to the <code>formula</code> argument of <code>scam</code>.</dd>
<dt>k</dt>
<dd>Number of knots.</dd>
<dt>len</dt>
<dd>If <code>NULL</code>, the default, <code>x</code> is used for prediction. Otherwise,
prediction is done over the range of <code>x</code> with <code>len</code> equidistant points.</dd>
<dt>sp</dt>
<dd>A vector of smoothing parameters passed on to <code>scam</code>.</dd></dl>

Arguments

Smooth a decreasing function. — decreasing_smoother

<dl>

<dt>x</dt>
<dd>The regressor passed on to the <code>formula</code> argument of <code>scam</code>.</dd>


<dt>y</dt>
<dd>The response passed on to the <code>formula</code> argument of <code>scam</code>.</dd>


<dt>k</dt>
<dd>Number of knots.</dd>


<dt>len</dt>
<dd>If <code>NULL</code>, the default, <code>x</code> is used for prediction. Otherwise,
prediction is done over the range of <code>x</code> with <code>len</code> equidistant points.</dd>


<dt>sp</dt>
<dd>A vector of smoothing parameters passed on to <code>scam</code>.</dd>

</dl>

decreasing_smoother: Smooth a decreasing function.

Description

Usage

Arguments