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