gam_interp

GAM interpolation using <code>mgcv:gam()</code>.

Animation of observed trajectories using spline-based interpolation (see for example, Buderman, F. E., Hooten, M. B., Ivan, J. S. and Shenk, T. M. (2016), <doi:10.1111/2041-210X.12465> "A functional model for characterizing long-distance movement behaviour". Methods Ecol Evol). Intended to be used exploratory data analysis, and perhaps for preparation of presentations.

Henry Scharf

anipaths

Animation of Multiple Trajectories with Uncertainty

Kristine Dinh

Rosales Hugo

Rivera Angelica

gam_interp function

<dl><dt>formula</dt>
<dd>optionally specify formula for <code><a href="/link/mgcv%3A%3Agam()?package=anipaths&version=0.10.5" data-mini-rdoc="anipaths::mgcv::gam()">mgcv::gam()</a></code> using <code>y</code> as response and <code>time</code> as predictor.</dd>
<dt>y</dt>
<dd>observations</dd>
<dt>time</dt>
<dd>times for observations</dd>
<dt>pred_times</dt>
<dd>prediction times</dd>
<dt>se.fit</dt>
<dd>logical default is <code>TRUE</code>; should standard pointwise errors be computed for interpolation</dd>
<dt>s_args</dt>
<dd>Arguments to <code><a href="/link/mgcv%3A%3As()?package=anipaths&version=0.10.5" data-mini-rdoc="anipaths::mgcv::s()">mgcv::s()</a></code> can be passed using a named list/vector.</dd>
<dt>uncertainty.type</dt>
<dd>State what type of uncertainty plot 1 is default for tails more than 1 is amount of predicted trajectories for each unique individual and blurs for blur plot</dd>
<dt>verbose</dt>
<dd>logical; <code>TRUE</code> prints messages about fitting details</dd></dl>

Arguments

GAM interpolation using mgcv:gam(). — gam_interp

<dl>

<dt>formula</dt>
<dd>optionally specify formula for <code><a href='https://rdrr.io/pkg/mgcv/man/gam.html'>mgcv::gam()</a></code> using <code>y</code> as response and <code>time</code> as predictor.</dd>


<dt>y</dt>
<dd>observations</dd>


<dt>time</dt>
<dd>times for observations</dd>


<dt>pred_times</dt>
<dd>prediction times</dd>


<dt>se.fit</dt>
<dd>logical default is <code>TRUE</code>; should standard pointwise errors be computed for interpolation</dd>


<dt>s_args</dt>
<dd>Arguments to <code><a href='https://rdrr.io/pkg/mgcv/man/s.html'>mgcv::s()</a></code> can be passed using a named list/vector.</dd>


<dt>uncertainty.type</dt>
<dd>State what type of uncertainty plot 1 is default for tails more than 1 is amount of predicted trajectories for each unique individual and blurs for blur plot</dd>


<dt>verbose</dt>
<dd>logical; <code>TRUE</code> prints messages about fitting details</dd>

</dl>

gam_interp: GAM interpolation using `mgcv:gam()`.

Description

Usage

Value

Arguments