View source: R/initial_guesses.R
check_growth_guess  R Documentation 
Generates a plot comparing a set of data points against the model prediction corresponding to an initial guess of the model parameters
check_growth_guess(
fit_data,
model_keys,
guess,
environment = "constant",
env_conditions = NULL,
approach = "single",
logbase_mu = 10,
formula = logN ~ time
)
fit_data 
Tibble (or data.frame) of data for the fit. It must have two columns, one with
the elapsed time ( 
model_keys 
Named the equations of the secondary model as in 
guess 
Named vector with the initial guess of the model parameters as in 
environment 
type of environment. Either "constant" (default) or "dynamic" (see below for details on the calculations for each condition) 
env_conditions 
Tibble describing the variation of the environmental
conditions for dynamic experiments. See 
approach 
whether "single" (default) or "global". Please see 
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.

A ggplot()
comparing the model prediction against the data
## Examples under constant environmental conditions 
## We need some 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 can directly plot the comparison for some values
check_growth_guess(my_data, list(primary = "modGompertz"),
c(logN0 = 1.5, mu = .8, lambda = 4, C = 3)
)
## Ot it can be combined with the automatic initial guess
check_growth_guess(my_data, list(primary = "modGompertz"),
make_guess_primary(my_data, "modGompertz")
)
## Examples under dynamic environmental conditions 
## We will use the datasets included in the package
data("example_dynamic_growth")
data("example_env_conditions")
## Model equations are assigned as in fit_growth
sec_models < list(temperature = "CPM", aw = "CPM")
## Guesses of model parameters are also defined as in fit_growth
guess < list(Nmax = 1e4,
N0 = 1e0, Q0 = 1e3,
mu_opt = 4,
temperature_n = 1,
aw_xmax = 1, aw_xmin = .9, aw_n = 1,
temperature_xmin = 25, temperature_xopt = 35,
temperature_xmax = 40, aw_xopt = .95
)
## We can now check our initial guess
check_growth_guess(example_dynamic_growth, sec_models, guess,
"dynamic",
example_env_conditions)
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