View source: R/fit_iso_growth.R
fit_isothermal_growth | R Documentation |
The function fit_isothermal_growth()
has been superseded by the top-level
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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