make_guess_primary: Initial guesses for fitting primary growth models

In biogrowth: Modelling of Population Growth

Initial guesses for fitting primary growth models

Description

The function uses some heuristics to provide initial guesses for the parameters of the growth model selected that can be used with fit_growth().

Usage

make_guess_primary(
  fit_data,
  primary_model,
  logbase_mu = 10,
  formula = logN ~ time
)

Arguments

fit_data	the experimental data. A tibble (or data.frame) with a column named time with the elapsed time and one called logN with the logarithm of the population size
primary_model	a string defining the equation of the primary model, as defined in primary_model_data()
logbase_mu	Base of the logarithm the growth rate is referred to. By default, 10 (i.e. log10). See vignette about units for details.
formula	an object of class "formula" describing the x and y variables. logN ~ time as a default.

Value

A named numeric vector of initial guesses for the model parameters

Examples

## An example of experimental data

my_data <- data.frame(time = 0:9, 
                      logN = c(2, 2.1, 1.8, 2.5, 3.1, 3.4, 4, 4.5, 4.8, 4.7))
                      
## We just need to pass the data and the model equation

make_guess_primary(my_data, "Logistic")

## We can use this together with fit_growth()

fit_growth(my_data,
           list(primary = "Logistic"),
           make_guess_primary(my_data, "Logistic"),
           c()
           )

## The parameters returned by the function are adapted to the model

make_guess_primary(my_data, "Baranyi")

## It can express mu in other logbases 

make_guess_primary(my_data, "Baranyi", logbase_mu = exp(1))  # natural
make_guess_primary(my_data, "Baranyi", logbase_mu = 2)  # base2

biogrowth documentation built on Aug. 19, 2023, 1:06 a.m.