multiple_conditions

This dataset is paired with multiple_counts to illustrate the global
fitting of <code>fit_growth()</code>.

datasets

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

multiple_conditions function

A nested list with two elements, each one corresponding to one experiment.
Each element is a data.frame with three columns:<ul>
<li>time: elapsed time</li>
<li>temperature: observed temperature</li>
<li>pH: observed pH</li>
</ul>

Format

Environmental conditions during several dynamic experiments — multiple_conditions

Environmental conditions during several dynamic experiments

multiple_conditions: Environmental conditions during several dynamic experiments

Description

Usage

Arguments

Format