fit_secondary_growth {biogrowth}  R Documentation 
Fit secondary growth models
Description
Fits a secondary growth model to a set of growth rates obtained experimentally. Modelling is done according to the gamma concept proposed by Zwietering (1992) and cardinal parameter models.
Usage
fit_secondary_growth(
fit_data,
starting_point,
known_pars,
sec_model_names,
transformation = "sq",
...,
check = TRUE,
formula = mu ~ .
)
Arguments
fit_data 
Tibble with the data used for the fit. It must have
one column with the observed growth rate (named 
starting_point 
Named vector with initial values for the model parameters
to estimate from the data. The growth rate under optimum conditions must be named

known_pars 
Named vector of fixed model parameters. Must be named using the
same convention as 
sec_model_names 
Named character vector defining the secondary model for each environmental factor. 
transformation 
Character defining the transformation of 
... 
Additional arguments passed to 
check 
Whether to do some basic checks (TRUE by default). 
formula 
an object of class "formula" describing the y variable. The
right hand side must be ".". By default 
Value
An instance of FitSecondaryGrowth()
.
Examples
## We use the data included in the package
data("example_cardinal")
## Define the models to fit
sec_model_names < c(temperature = "Zwietering", pH = "CPM")
## Any model parameter can be fixed
known_pars < list(mu_opt = 1.2, temperature_n = 1,
pH_n = 2, pH_xmax = 6.8, pH_xmin = 5.2)
## Initial values must be given for every other parameter
my_start < list(temperature_xmin = 5, temperature_xopt = 35,
pH_xopt = 6.5)
## We can now call the fitting function
fit_cardinal < fit_secondary_growth(example_cardinal, my_start, known_pars, sec_model_names)
## With summary, we can look at the parameter estimates
summary(fit_cardinal)
## The plot function compares predictions against observations
plot(fit_cardinal)
## Passing which = 2, generates a different kind of plot
plot(fit_cardinal, which = 2)
plot(fit_cardinal, which = 2, add_trend = TRUE)
plot(fit_cardinal, which = 2, add_segment = TRUE)