R: Asymptotic regression model

AR {drc} | R Documentation

## Asymptotic regression model

### Description

Providing the mean function and the corresponding self starter function for the asymptotic regression model.

### Usage

      AR.2(fixed = c(NA, NA), names = c("d", "e"), ...)

      AR.3(fixed = c(NA, NA, NA), names = c("c", "d", "e"), ...)

### Arguments

`fixed` | numeric vector. Specifies which parameters are fixed and at what value they are fixed. NAs for parameter that are not fixed.
`names` | vector of character strings giving the names of the parameters (should not contain ":").
`...` | additional arguments to be passed from the convenience functions.

### Details

The asymptotic regression model is a three-parameter model with mean function:

f(x) = c + (d-c)(1-\exp(-x/e))

The parameter c is the lower limit (at x=0), the parameter d is the upper limit and the parameter e>0 is determining the steepness of the increase as x.

### Value

A list of class `drcMean`, containing the mean function, the self starter function, the parameter names and other components such as derivatives and a function for calculating ED values.

### Note

The functions are for use with the function `drm`.

### Author(s)

Christian Ritz

### See Also

A very similar, but monotonously decreasing model is the exponential decay model: `EXD.2` and `EXD.3`.

### Examples

    ## First model
    met.as.m1<-drm(gain ~ dose, product, data = methionine, fct = AR.3(),
    pmodels = list(~1, ~factor(product), ~factor(product)))
    plot(met.as.m1, log = "", ylim = c(1450, 1800))
    summary(met.as.m1)

    ## Calculating bioefficacy: approach 1
    coef(met.as.m1)[5] / coef(met.as.m1)[4] * 100

    ## Calculating bioefficacy: approach 2
    EDcomp(met.as.m1, c(50,50))

    ## Simplified models
    met.as.m2<-drm(gain ~ dose, product, data = methionine, fct = AR.3(),
    pmodels = list(~1, ~1, ~factor(product)))
    anova(met.as.m2, met.as.m1)  # simplification not possible

    met.as.m3 <- drm(gain ~ dose, product, data = methionine, fct = AR.3(),
    pmodels = list(~1, ~factor(product), ~1))
    anova(met.as.m3, met.as.m1)  # simplification not possible

[Package drc version 3.0-1 Index]