statforbiology (version 0.9.9)

SSL: Logistic equations

Description

These functions provide the logistic equations with 4 (L4.fun), 3 (L3.fun) and 2 (L2.fun) parameters with self-starter for the nls function (NLS.L4, NLS.L3 and NLS.L2) and the self-starter for logistic function with two parameters for the drm function in the drc package (DRC.L2).

Usage

L4.fun(predictor, b, c, d, e)
L3.fun(predictor, b, d, e)
L2.fun(predictor, b, e)
NLS.L4(predictor, b, c, d, e)
NLS.L3(predictor, b, d, e)
NLS.L2(predictor, b, e)
DRC.L2(upper = 1, fixed = c(NA, NA), names = c("b", "e"))

Value

L4.fun, L3.fun, L2.fun, NLS.L4, NLS.L3 and NLS.L2 return a numeric value, while DRC.L2 returns a list containing the nonlinear function, the self starter function and the parameter names.

Arguments

predictor

a numeric vector of values at which to evaluate the model

b

model parameter (slope at inflection point)

c

model parameter (lower asymptote)

d

model parameter (higher asymptote)

e

model parameter (abscissa at inflection point)

upper

numeric. For L.2, a upper asymptote different from 1 can be specified.

fixed

numeric vector. Specifies which parameters are fixed and at what value they are fixed. NAs for parameter that are not fixed.

names

names. A vector of character strings giving the names of the parameters. The default is reasonable.

Author

Andrea Onofri

Details

The logistic equation is parameterised as: $$ f(x) = c + \frac{d - c}{1+exp\left[-b(x - e)\right]} $$ for the 3- and 2-parameter model c is equal to 0, while for the 2-parameter model d is equal to 1.

Examples

data(beetGrowth)
mod3 <- nls(weightInf ~ NLS.L3(DAE, b, c, d), data = beetGrowth)
mod3b <- drm(weightInf ~ DAE, fct=DRC.L2(upper = 25), data = beetGrowth)