meanFilter

Data collected on movement behavior is often in the form of time-
stamped latitude/longitude coordinates sampled from the underlying movement
behavior. These data can be compressed into a set of segments via the Top-
Down Time Ratio Segmentation method described in Meratnia and de By (2004)
<doi:10.1007/978-3-540-24741-8_44> which, with some loss of information,
can both reduce the size of the data as well as provide corrective smoothing
mechanisms to help reduce the impact of measurement error. This is an
improvement on the well-known Douglas-Peucker algorithm for segmentation
that operates not on the basis of perpendicular distances. Top-Down Time
Ratio segmentation allows for disparate sampling time intervals by
calculating the distance between locations and segments with respect to
time. Provided a trajectory with timestamps, tdtr() returns a set of straight-
line segments that can represent the full trajectory. McCool, Lugtig,
and Schouten (2022) <doi:10.1007/s11116-022-10328-2> describe this method as
implemented here in more detail.

Danielle McCool

topdowntimeratio

Top-Down Time Ratio Segmentation for Coordinate Trajectories

meanFilter function

<dl><dt>coord</dt>
<dd>A vector of coordinates over which to apply a mean filter</dd>
<dt>n</dt>
<dd>The number of values to average</dd></dl>

Arguments

Mean filter — meanFilter

<dl>

<dt>coord</dt>
<dd>A vector of coordinates over which to apply a mean filter</dd>


<dt>n</dt>
<dd>The number of values to average</dd>

</dl>

meanFilter: Mean filter

Description

Usage

Value

Arguments