neg_log_likelihood_lognormal

Calculates the negative log-likelihood for observed final weights
assuming they follow a log-normal distribution around the predicted weight.
Consistent with the TMB backend implementation.

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

neg_log_likelihood_lognormal function

<dl><dt>params</dt>
<dd>Vector of parameters to estimate:
- params[1]: p_value (feeding level, 0.01-5.0)
- params[2]: log(sigma) (log of standard deviation of log-weights)</dd>
<dt>observed_weights</dt>
<dd>Numeric vector of observed final weights (g)</dd>
<dt>simulation_function</dt>
<dd>Function that takes p_value and returns predicted weight</dd></dl>

Arguments

Calculate negative log-likelihood for log-normal weight observations — neg_log_likelihood_lognormal

<dl>

<dt>params</dt>
<dd>Vector of parameters to estimate:
- params[1]: p_value (feeding level, 0.01-5.0)
- params[2]: log(sigma) (log of standard deviation of log-weights)</dd>


<dt>observed_weights</dt>
<dd>Numeric vector of observed final weights (g)</dd>


<dt>simulation_function</dt>
<dd>Function that takes p_value and returns predicted weight</dd>

</dl>

neg_log_likelihood_lognormal: Calculate negative log-likelihood for log-normal weight observations

Description

Usage

Value

Arguments