choose_lag_fit_algorithm_logistic {miLAG}

choose_lag_fit_algorithm_logistic

Description

Runs nlsLM/nls algorithms with three different parameter setups to fit the best Logistic model parameters to our data and chooses the best model

Usage

choose_lag_fit_algorithm_logistic(
  gr_curve,
  n0,
  init_gr_rate = init_gr_rate,
  init_K = init_K,
  init_lag = init_lag,
  max_iter = 100,
  lower_bound = c(0, 0, 0)
)

Arguments

gr_curve

data from one specific growth curve with the following columns: LOG10N, t

n0

the initial biomass

init_gr_rate

initial value for the growth rate

init_K

initial value for the saturation parameter K

init_lag

initial value for the lag parameter

max_iter

max. number of iterations; defaults to 100

lower_bound

lower bound for the bounded nls optimization; defaults to 0

Value

the best nls fitting object with parameters fitted to logistic model (lowest Res.Sum Sq provided that all coefficients are nonnegative)