plot_convergence

Plots the criterion value on each of the steps of the algorithm, both for optimizing weights and points,
against the total step number.

Calculates D-, Ds-, A-, I- and L-optimal designs for non-linear models, via an implementation of the cocktail algorithm (Yu, 2011, <doi:10.1007/s11222-010-9183-2>). Compares designs via their efficiency, and augments any design with a controlled efficiency. An efficient rounding function has been provided to transform approximate designs to exact designs.

Carlos de la Calle-Arroyo

optedr

Calculating Optimal and D-Augmented Designs

Jesús López-Fidalgo

Licesio J. Rodríguez-Aragón

plot_convergence function

<dl><dt>convergence</dt>
<dd>A dataframe with two columns:<ul>
<li><code>criteria</code> contains value of the criterion on each step.</li>
<li><code>step</code> contains number of the step.</li>
</ul></dd></dl>

Arguments

Plot Convergence of the algorithm — plot_convergence

<dl>

<dt>convergence</dt>
<dd>A dataframe with two columns:<ul>
<li><code>criteria</code> contains value of the criterion on each step.</li>
<li><code>step</code> contains number of the step.</li>
</ul></dd>

</dl>

plot_convergence: Plot Convergence of the algorithm

Description

Usage

Value

Arguments