logistic: The logistic model
In MaximeBSanofi/drc2:

Description Usage Arguments Details Value Author(s) Examples

The general asymmetric five-parameter logistic model for describing dose-response relationships.

  logistic(fixed = c(NA, NA, NA, NA, NA), names = c("b", "c", "d", "e", "f"),
  method = c("1", "2", "3", "4"), ssfct = NULL, 
  fctName, fctText) 

  L.3(fixed = c(NA, NA, NA), names = c("b", "d", "e"), ...)
  L.4(fixed = c(NA, NA, NA, NA), names = c("b", "c", "d", "e"), ...)
  L.5(fixed = c(NA, NA, NA, NA, NA), names = c("b", "c", "d", "e", "f"), ...)

`fixed`	numeric vector. Specifies which parameters are fixed and at what value they are fixed. NAs for parameter that are not fixed.
`names`	a vector of character strings giving the names of the parameters (should not contain ":"). The order of the parameters is: b, c, d, e, f (see under 'Details').
`method`	character string indicating the self starter function to use.
`ssfct`	a self starter function to be used.
`fctName`	optional character string used internally by convenience functions.
`fctText`	optional character string used internally by convenience functions.
`...`	Additional arguments (see `llogistic`).

The default arguments yields the five-parameter logistic mean function given by the expression

f(x) = c + \frac{d-c}{(1+\exp(b(x - e)))^f}

The model is different from the log-logistic models llogistic and llogistic2 where the term

log(x)

is used instead of

The model is sometimes referred to as the Boltzmann model.

The value returned is a list containing the nonlinear function, the self starter function and the parameter names.

Christian Ritz

## Fitting the four-parameter logistic model
ryegrass.m1 <- drm(rootl ~ conc, data = ryegrass, fct = L.4())
summary(ryegrass.m1)

## Fitting an asymmetric logistic model
##  requires installing the package 'NISTnls'
# Ratkowsky3.m1 <- drm(y~x, data = Ratkowsky3, 
# fct = L.5(fixed = c(NA, 0, NA, NA, NA)))
# plot(Ratkowsky3.m1)
# summary(Ratkowsky3.m1)  
## okay agreement with NIST values
##  for the two parameters that are the same