miLAG (version 1.0.5)

choose_lag_fit_algorithm_baranyi: choose_lag_fit_algorithm_baranyi

Description

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

Usage

choose_lag_fit_algorithm_baranyi(
  gr_curve,
  LOG10N0,
  init_lag,
  init_mumax,
  init_LOG10Nmax,
  max_iter,
  lower_bound
)

Value

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

Arguments

gr_curve

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

LOG10N0

init value for the LOG10N0 parameter

init_lag

initial value for the lag

init_mumax

initial value for the mumax parameter

init_LOG10Nmax

initial value for the LOG10Nmax parameter

max_iter

max. number of iterations

lower_bound

lower bound for the bounded nls optimization;