mle_estimate_p_value_lognormal

Estimates p_value and uncertainty using observed final weights
with a frequentist likelihood approach assuming log-normal weight distribution.

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

mle_estimate_p_value_lognormal function

<dl><dt>observed_weights</dt>
<dd>Vector of observed final weights</dd>
<dt>simulation_function</dt>
<dd>Function that runs simulation and returns weight</dd>
<dt>estimate_sigma</dt>
<dd>Whether to estimate sigma or use fixed value</dd>
<dt>fixed_sigma</dt>
<dd>Fixed sigma value (if estimate_sigma = FALSE)</dd></dl>

Arguments

Maximum Likelihood Estimation for p_value using log-normal distribution — mle_estimate_p_value_lognormal

<dl>

<dt>observed_weights</dt>
<dd>Vector of observed final weights</dd>


<dt>simulation_function</dt>
<dd>Function that runs simulation and returns weight</dd>


<dt>estimate_sigma</dt>
<dd>Whether to estimate sigma or use fixed value</dd>


<dt>fixed_sigma</dt>
<dd>Fixed sigma value (if estimate_sigma = FALSE)</dd>

</dl>

mle_estimate_p_value_lognormal: Maximum Likelihood Estimation for p_value using log-normal distribution

Description

Usage

Value

Arguments