SSasympOff
Self-Starting Nls Asymptotic Regression Model with an Offset
This selfStart model evaluates an alternative parametrization
of the asymptotic
regression function and the gradient with respect to those parameters.
It has an initial
attribute that creates initial estimates of the parameters
Asym, lrc, and c0.
- Keywords
- models
Usage
SSasympOff(input, Asym, lrc, c0)Arguments
- input
- a numeric vector of values at which to evaluate the model.
- Asym
- a numeric parameter representing the horizontal asymptote on
the right side (very large values of
input). - lrc
- a numeric parameter representing the natural logarithm of the rate constant.
- c0
- a numeric parameter representing the
inputfor which the response is zero.
Value
-
a numeric vector of the same length as
input. It is the value of
the expression Asym*(1 - exp(-exp(lrc)*(input - c0))). If all of
the arguments Asym, lrc, and c0 are
names of objects, the gradient matrix with respect to these names is
attached as an attribute named gradient.
See Also
nls, selfStart;
example(SSasympOff) gives graph showing the SSasympOff
parametrization, where $phi_1$ is Asymp,
$phi_3$ is c0.
Examples
library(stats)
CO2.Qn1 <- CO2[CO2$Plant == "Qn1", ]
SSasympOff(CO2.Qn1$conc, 32, -4, 43) # response only
Asym <- 32; lrc <- -4; c0 <- 43
SSasympOff(CO2.Qn1$conc, Asym, lrc, c0) # response and gradient
getInitial(uptake ~ SSasympOff(conc, Asym, lrc, c0), data = CO2.Qn1)
## Initial values are in fact the converged values
fm1 <- nls(uptake ~ SSasympOff(conc, Asym, lrc, c0), data = CO2.Qn1)
summary(fm1)
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