fplogistic: Fractional polynomial-logistic dose-response models
In MaximeBSanofi/drc2:

Description Usage Arguments Details Value Author(s) References See Also

Model function for specifying dose-response models that are a combination of a logistic model and an appropriate class of fractional polynomials.

fplogistic(p1, p2, fixed = c(NA, NA, NA, NA), names = c("b", "c", "d", "e"), 
method = c("1", "2", "3", "4"), ssfct = NULL, fctName, fctText)

FPL.4(p1, p2, fixed = c(NA, NA, NA, NA), names = c("b", "c", "d", "e"), ...)

`p1`	numeric denoting the negative power of log(dose+1) in the fractional polynomial.
`p2`	numeric denoting the positive power of log(dose+1) in the fractional polynomial.
`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 default is reasonable (see under 'Usage'). 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 `fplogistic`).

The fractional polynomial dose-response models introduced by Namata et al. (2008) are implemented using the logistic model as base.

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

Christian Ritz

Namata, Harriet and Aerts, Marc and Faes, Christel and Teunis, Peter (2008) Model Averaging in Microbial Risk Assessment Using Fractional Polynomials, Risk Analysis 28, 891–905.

Examples are found maED.

MaximeBSanofi/drc2 documentation built on Feb. 22, 2022, 12:02 a.m.