fit_mean_closed

Fits an elastic mean for open curves. Is usually called from
<code>compute_elastic_mean</code>.

Provides functions to align curves and to compute mean curves based on the
elastic distance defined in the square-root-velocity framework. For more details on
this framework see Srivastava and Klassen (2016, <doi:10.1007/978-1-4939-4020-2>).
For more theoretical details on our methods and algorithms see
Steyer et al. (2023, <doi:10.1111/biom.13706>) and Steyer et al. (2023, <arXiv:2305.02075>).

Lisa Steyer

elasdics

Elastic Analysis of Sparse, Dense and Irregular Curves

fit_mean_closed function

<dl><dt>srv_data_curves</dt>
<dd>list of <code>data.frame</code>s with srv vectors in each row.
Usually a result of a call to <code>get_srv_from_points</code></dd>
<dt>knots</dt>
<dd>set of knots for the mean spline curve</dd>
<dt>max_iter</dt>
<dd>maximal number of iterations</dd>
<dt>type</dt>
<dd>if "smooth" linear srv-splines are used which results in a differentiable mean curve</dd>
<dt>eps</dt>
<dd>the algorithm stops if L2 norm of coefficients changes less</dd>
<dt>pen_factor</dt>
<dd>penalty factor forcing the mean to be closed
if "polygon" the mean will be piecewise linear.</dd></dl>

Arguments

Fitting function for open curves — fit_mean_closed

<dl>

<dt>srv_data_curves</dt>
<dd>list of <code>data.frame</code>s with srv vectors in each row.
Usually a result of a call to <code>get_srv_from_points</code></dd>


<dt>knots</dt>
<dd>set of knots for the mean spline curve</dd>


<dt>max_iter</dt>
<dd>maximal number of iterations</dd>


<dt>type</dt>
<dd>if "smooth" linear srv-splines are used which results in a differentiable mean curve</dd>


<dt>eps</dt>
<dd>the algorithm stops if L2 norm of coefficients changes less</dd>


<dt>pen_factor</dt>
<dd>penalty factor forcing the mean to be closed
if "polygon" the mean will be piecewise linear.</dd>

</dl>

fit_mean_closed: Fitting function for open curves

Description

Usage

Value

Arguments