calc_lagistic_fit_lag: calc_lagistic_fit_lag

View source: R/milags_functions.R

calc_lagistic_fit_lagR 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


miLAG documentation built on April 3, 2025, 8:09 p.m.