run_robust_optimization

Advanced optimization routine with automatic fallback strategies,
multiple starting points, and comprehensive error handling.
Works for both basic and hierarchical models.

internal

An implementation of the 'Fish Bioenergetics 4.0' framework
described in Deslauriers et al. (2017)
<doi:10.1080/03632415.2017.1377558>. Provides automated parameter
optimization, multi-prey diet modeling, and comprehensive energy budget
simulations for fisheries research and aquaculture applications. An
optional 'TMB' (Template Model Builder) backend delivers 10-50x speedup
in maximum likelihood estimation while maintaining full backward
compatibility. Includes species-specific parameter databases and tools
for modeling fish growth, consumption, and metabolism under varying
environmental conditions.

Hans Ttito

fb4package

'Fish Bioenergetics 4.0' Model Implementation with
High-Performance 'TMB' Backend

run_robust_optimization function

<dl><dt>obj</dt>
<dd>TMB objective function</dd>
<dt>method</dt>
<dd>Primary optimization method ("nlminb" or "optim")</dd>
<dt>lower</dt>
<dd>Lower parameter bounds (log scale)</dd>
<dt>upper</dt>
<dd>Upper parameter bounds (log scale)</dd>
<dt>max_iter</dt>
<dd>Maximum iterations</dd>
<dt>tolerance</dt>
<dd>Convergence tolerance</dd>
<dt>n_restarts</dt>
<dd>Number of random restarts if primary fails</dd>
<dt>verbose</dt>
<dd>Show optimization progress</dd>
<dt>...</dt>
<dd>Additional arguments passed to optimization function</dd></dl>

Arguments

Run robust optimization with multiple fallback strategies — run_robust_optimization

<dl>

<dt>obj</dt>
<dd>TMB objective function</dd>


<dt>method</dt>
<dd>Primary optimization method ("nlminb" or "optim")</dd>


<dt>lower</dt>
<dd>Lower parameter bounds (log scale)</dd>


<dt>upper</dt>
<dd>Upper parameter bounds (log scale)</dd>


<dt>max_iter</dt>
<dd>Maximum iterations</dd>


<dt>tolerance</dt>
<dd>Convergence tolerance</dd>


<dt>n_restarts</dt>
<dd>Number of random restarts if primary fails</dd>


<dt>verbose</dt>
<dd>Show optimization progress</dd>


<dt>...</dt>
<dd>Additional arguments passed to optimization function</dd>

</dl>

run_robust_optimization: Run robust optimization with multiple fallback strategies

Description

Usage

Value

Arguments