FIM_logistic_2pred

It provides the cpp function for FIM for the following model: 
 <code>~exp(b0+ b1 * x1 + b2 * x2 + b3 * x1 * x2)/(1 + exp(b0 + b1 * x1 + b2 * x2 + b3 * x1 * x2))</code>.

Finds optimal designs for nonlinear models using a metaheuristic algorithm called Imperialist Competitive Algorithm (ICA). See, for details, Masoudi et al. (2022) <doi:10.32614/RJ-2022-043>, Masoudi et al. (2017) <doi:10.1016/j.csda.2016.06.014> and Masoudi et al. (2019) <doi:10.1080/10618600.2019.1601097>.

Ehsan Masoudi

ICAOD

Optimal Designs for Nonlinear Models via ICA

Heinz Holling

Weng Kee Wong

Seongho Kim

FIM_logistic_2pred function

<dl><dt>x1</dt>
<dd>Vector of design points (for first predictor).</dd>
<dt>x2</dt>
<dd>Vector of design points (for second predictor).</dd>
<dt>w</dt>
<dd>Vector of design weight. Its length must be equal to the length of <code>x</code> and <code>sum(w) = 1</code>.</dd>
<dt>param</dt>
<dd>Vector of values for the model parameters <code>c(b0, b1, b2, b3)</code>.</dd></dl>

Arguments

It provides the cpp function for FIM for the following model: 
 <code>~exp(b0+ b1 * x1 + b2 * x2 + b3 * x1 * x2)/(1 + exp(b0 + b1 * x1 + b2 * x2 + b3 * x1 * x2))</code>.

Fisher Information Matrix for the Logistic Model with Two Predictors — FIM_logistic_2pred

<dl>

<dt>x1</dt>
<dd>Vector of design points (for first predictor).</dd>


<dt>x2</dt>
<dd>Vector of design points (for second predictor).</dd>


<dt>w</dt>
<dd>Vector of design weight. Its length must be equal to the length of <code>x</code> and <code>sum(w) = 1</code>.</dd>


<dt>param</dt>
<dd>Vector of values for the model parameters <code>c(b0, b1, b2, b3)</code>.</dd>

</dl>

FIM_logistic_2pred: Fisher Information Matrix for the Logistic Model with Two Predictors

Description

Usage

Value

Arguments