smoother

A wrapper for the stats::loess function, with default parameters suitable for smoothing raw eye data

Enables the automation of actions across the pipeline, including
initial steps of transforming binocular data and gap repair to event-based
processing such as fixations, saccades, and entry/duration in Areas of
Interest (AOIs). It also offers visualisation of eye movement and AOI
entries. These tools take relatively raw (trial, time, x, and y form) data
and can be used to return fixations, saccades, and AOI entries and time spent
in AOIs. As the tools rely on this basic data format, the functions can work
with data from any eye tracking device. Implements fixation and saccade
detection using methods proposed by Salvucci and Goldberg (2000)
<doi:10.1145/355017.355028>.

Tom Beesley

eyetools

Analyse Eye Data

Matthew Ivory

smoother function

<dl><dt>data</dt>
<dd>A dataframe with raw data (time, x, y, trial) for one participant</dd>
<dt>span</dt>
<dd>From stats::loess. The parameter alpha which controls the degree of smoothing.</dd>
<dt>plot</dt>
<dd>whether to plot the raw and smoothed plot for inspection</dd></dl>

Arguments

Smoothing of raw data — smoother

<dl>

<dt>data</dt>
<dd>A dataframe with raw data (time, x, y, trial) for one participant</dd>


<dt>span</dt>
<dd>From stats::loess. The parameter alpha which controls the degree of smoothing.</dd>


<dt>plot</dt>
<dd>whether to plot the raw and smoothed plot for inspection</dd>

</dl>

smoother: Smoothing of raw data

Description

Usage

Value

Arguments

Details

Examples