calc_lagistic_fit_lag {miLAG} | R Documentation |
calc_lagistic_fit_lag
Description
Calculates lag based on fitting logistic model to data
Usage
calc_lagistic_fit_lag(
data,
n0,
init_gr_rate = NULL,
init_K = NULL,
init_lag = NULL,
algorithm,
max_iter,
return_all_params = FALSE,
min_b = 0.2,
min_a = 0.8
)
Arguments
data |
a data frame with two required columns names: "time" and "biomass",and one optional column: "curve_id" This is data from may come from multiple growth curves |
n0 |
a data frame describing initial biomass for each of the curves, i.e. it has two obligatory columns: "curve_id", "N0" |
init_gr_rate |
initial value for the growth rate, defaults to NULL in which case it will be approximated based on the data |
init_K |
initial value for the saturation parameter K, defaults to NULL in which case it will be approximated based on the data |
init_lag |
initial value for the lag parameter, defaults to NULL in which case it will be approximated based on the data |
algorithm |
eg. "auto", "Levenberg-Marquardt", "port" |
max_iter |
Maximum number of iterations |
return_all_params |
defaults to FALSE, TRUE if you also want to get K and growth.rate apart from lag |
min_b |
defaults to 0.2; mina and minb define where to look for exponential phase: it will be where the biomass is between min + (max-min)*(lower.bound.for.gr TO upper.bound.for.gr) |
min_a |
defaults to 0.8 |
Value
growth curve data with additional columns ('lag', and predicted biomass 'predicted'), and the fitting object if return.all.params was set to TRUE