get_secondary_residuals

Residual function for <code>fit_secondary_growth()</code>.

Modelling of population growth under static and dynamic environmental conditions.
Includes functions for model fitting and making prediction under isothermal and
dynamic conditions. The methods (algorithms & models) are based on
predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)).

Alberto Garre

biogrowth

Modelling of Population Growth

Jeroen Koomen

Heidy den Besten

Marcel Zwietering

get_secondary_residuals function

<dl><dt>this_p</dt>
<dd>Named vector of model parameter values.</dd>
<dt>my_data</dt>
<dd>Tibble with the data used for the fit.</dd>
<dt>known_pars</dt>
<dd>Named vector of fixed model paramaters.</dd>
<dt>sec_model_names</dt>
<dd>Named character vector defining the secondary model
for each environmental factor.</dd>
<dt>transformation</dt>
<dd>Character defining the tranformation of <code>mu</code> for
model fitting. One of <code>sq</code> (square root), <code>log</code> (log-transform) or
<code>none</code> (no transformation).</dd></dl>

Arguments

Residuals of secondary models — get_secondary_residuals

<dl>

<dt>this_p</dt>
<dd>Named vector of model parameter values.</dd>


<dt>my_data</dt>
<dd>Tibble with the data used for the fit.</dd>


<dt>known_pars</dt>
<dd>Named vector of fixed model paramaters.</dd>


<dt>sec_model_names</dt>
<dd>Named character vector defining the secondary model
for each environmental factor.</dd>


<dt>transformation</dt>
<dd>Character defining the tranformation of <code>mu</code> for
model fitting. One of <code>sq</code> (square root), <code>log</code> (log-transform) or
<code>none</code> (no transformation).</dd>

</dl>

get_secondary_residuals: Residuals of secondary models

Description

Usage

Value

Arguments