goodness_of_fit

Generates a table with several statistical indexes describing the
quality of the model fit:<ul>
<li>ME: Mean Error.</li>
<li>RMSE: Root Mean Squared Error.</li>
<li>loglik: log-likelihood.</li>
<li>AIC: Akaike Information Criterion.</li>
<li>AICc: Akaike Information Criterion with correction for
finite sample size.</li>
<li>BIC: Bayesian Infromation Criterion.</li>
<li>Af: Accuracy factor.</li>
<li>Bf: Bias factor.</li>
</ul>

Functions for modelling microbial inactivation under
isothermal or dynamic conditions. The calculations are based on several mathematical models broadly
used by the scientific community and industry. Functions enable to make predictions for cases where the
kinetic parameters are known. It also implements functions for parameter estimation for isothermal and
dynamic conditions. The model fitting capabilities include an Adaptive Monte Carlo method for a Bayesian
approach to parameter estimation.

Alberto Garre

bioinactivation

Mathematical Modelling of (Dynamic) Microbial Inactivation

Pablo S. Fernandez

Jose A. Egea

goodness_of_fit function

<dl><dt>object</dt>
<dd>A model fit generated by bioinactivation</dd></dl>

Arguments

Goodness of fit for microbial inactivation models — goodness_of_fit

<dl>

<dt>object</dt>
<dd>A model fit generated by bioinactivation</dd>

</dl>

goodness_of_fit: Goodness of fit for microbial inactivation models

Description

Usage

Arguments