update_design_total

Takes a design and merge together all points that are closer between them than a certain threshold <code>delta</code>.

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

update_design_total function

<dl><dt>design</dt>
<dd>The design to update. It's a dataframe with two columns:<ul>
<li><code>Point</code> contains the support points of the design.</li>
<li><code>Weight</code> contains the corresponding weights of the <code>Point</code>s.</li>
</ul></dd>
<dt>delta</dt>
<dd>Threshold which defines how close two points have to be to any of the existing ones in order to
merge with them.</dd></dl>

Arguments

Merge close points of a design — update_design_total

<dl>

<dt>design</dt>
<dd>The design to update. It's a dataframe with two columns:<ul>
<li><code>Point</code> contains the support points of the design.</li>
<li><code>Weight</code> contains the corresponding weights of the <code>Point</code>s.</li>
</ul></dd>


<dt>delta</dt>
<dd>Threshold which defines how close two points have to be to any of the existing ones in order to
merge with them.</dd>

</dl>

update_design_total: Merge close points of a design

Description

Usage

Value

Arguments