sd_via_median_estimator

Compute standard deviation via median estimator.
Please refer to formula #2 in Engbert &amp; Kliegl (2003).
Falls back on mean estimator, if computed standard deviation
is smaller than <code>.Machine$double.eps</code>. Raises an error
if the results using the mean estimator is still smaller than
<code>.Machine$double.eps</code>.

A modular and extendable approach to extract (micro)saccades from gaze samples via an ensemble of methods.
Although there is an agreement about a general definition of a saccade, the more specific details are harder to agree upon.
Therefore, there are numerous algorithms that extract saccades based on various heuristics, which differ in the assumptions about velocity,
acceleration, etc. The package uses three methods (Engbert and Kliegl (2003) <doi:10.1016/S0042-6989(03)00084-1>,
Otero-Millan et al. (2014)<doi:10.1167/14.2.18>, and Nyström and Holmqvist (2010) <doi:10.3758/BRM.42.1.188>)
to label individual samples and then applies a majority vote approach to identify saccades. The package includes three
methods but can be extended via custom functions. It also uses a modular approach to compute velocity and
acceleration from noisy samples. Finally, you can obtain methods votes per gaze sample instead of saccades.

Alexander (Sasha) Pastukhov

saccadr

Extract Saccades via an Ensemble of Methods Approach

Alexander Pastukhov

sd_via_median_estimator function

<dl><dt>x</dt>
<dd>Numeric values</dd>
<dt>na.rm</dt>
<dd>Whether to exclude NA values, defaults to <code>FALSE</code>.</dd></dl>

Arguments

Compute standard deviation via median estimator. — sd_via_median_estimator

<dl>

<dt>x</dt>
<dd>Numeric values</dd>


<dt>na.rm</dt>
<dd>Whether to exclude NA values, defaults to <code>FALSE</code>.</dd>

</dl>

sd_via_median_estimator: Compute standard deviation via median estimator.

Description

Usage

Value

Arguments

Examples