View source: R/fit_iso_growth.R
fit_isothermal_growth  R Documentation 
The function fit_isothermal_growth()
has been superseded by the toplevel
function fit_growth()
, which provides a unified approach for growth modelling.
Nonetheless, it can still fit a primary growth model to data obtained under static environmental conditions.
fit_isothermal_growth(
fit_data,
model_name,
starting_point,
known_pars,
...,
check = TRUE,
formula = logN ~ time,
logbase_mu = logbase_logN,
logbase_logN = 10
)
fit_data 
Tibble of data for the fit. It must have two columns, one with
the elapsed time ( 
model_name 
Character defining the primary growth model 
starting_point 
Named vector of initial values for the model parameters. 
known_pars 
Named vector of known model parameters (not fitted). 
... 
Additional arguments passed to 
check 
Whether to do some basic checks (TRUE by default). 
formula 
an object of class "formula" describing the x and y variables.

logbase_mu 
Base of the logarithm the growth rate is referred to. By default, the same as logbase_logN. See vignette about units for details. 
logbase_logN 
Base of the logarithm for the population size. By default, 10 (i.e. log10). See vignette about units for details. 
An instance of FitIsoGrowth()
.
## Some dummy data
library(tibble)
my_data < tibble(time = c(0, 25, 50, 75, 100),
logN = c(2, 2.5, 7, 8, 8))
## Choose the model
my_model < "Baranyi"
## Initial values for the model parameters
start = c(logNmax = 8, lambda = 25, logN0 = 2)
## Any model parameter can be fixed
known < c(mu = .2)
## Now, we can call the function
static_fit < fit_isothermal_growth(my_data, my_model, start, known)
summary(static_fit)
## We can plot the fitted model against the observations
plot(static_fit)
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