fit_growthmodel: Fit Nonlinear Parametric Growth Model

In growthrates: Estimate Growth Rates from Experimental Data

Fit Nonlinear Parametric Growth Model

Description

Determine maximum growth rates by fitting nonlinear models.

Usage

fit_growthmodel(
  FUN,
  p,
  time,
  y,
  lower = -Inf,
  upper = Inf,
  which = names(p),
  method = "Marq",
  transform = c("none", "log"),
  control = NULL,
  ...
)

Arguments

FUN	function of growth model to be fitted.
p	named vector of start parameters and initial values of the growth model.
time	vector of independent variable.
y	vector of dependent variable (concentration of organisms).
lower	lower bound of the parameter vector (optional).
upper	upper bound of the parameter vector (optional).
which	vector of parameter names that are to be fitted.
method	character vector specifying the optimization algorithm (see modFit).
transform	fit model to non-transformed or log-transformed data.
control	A list of control parameters for the optimizers. See Details.
...	additional parameters passed to the optimizer.

Details

This function calls modFit from package FME. Syntax of control parameters and available options may differ, depending on the optimizer used, except control=list(trace=...) that switches tracing on and off for all methods and is either TRUE, or FALSE, or an integer value like 0, 1, 2, 3, depending on the optimizer.

Value

object with parameters of the fit.

See Also

modFit about constrained fitting of models to data

Other fitting functions: all_easylinear(), all_growthmodels(), all_splines(), fit_easylinear(), fit_spline()

Examples

data(bactgrowth)
splitted.data <- multisplit(bactgrowth, c("strain", "conc", "replicate"))

## get one element either by index or by name
dat <- splitted.data[[1]]
dat <- splitted.data[["D:0:1"]]

p <- c(y0 = 0.01, mumax = 0.2, K = 0.1)

## unconstraied fitting
fit1 <- fit_growthmodel(FUN = grow_logistic, p = p, dat$time, dat$value)
coef(fit1)
summary(fit1)

## optional box-constraints
lower <- c(y0 = 1e-6, mumax = 0,   K = 0)
upper <- c(y0 = 0.05, mumax = 5,   K = 0.5)
fit1 <- fit_growthmodel(
  FUN = grow_logistic, p = p, dat$time, dat$value,
  lower = lower, upper = upper)

plot(fit1, log="y")

growthrates documentation built on Oct. 4, 2022, 1:06 a.m.