| SSgompertz | R Documentation |
This selfStart model evaluates the Gompertz growth model
and its gradient. It has an initial attribute that
creates initial estimates of the parameters Asym,
b2, and b3.
SSgompertz(x, Asym, b2, b3)
x |
a numeric vector of values at which to evaluate the model. |
Asym |
a numeric parameter representing the asymptote. |
b2 |
a numeric parameter related to the value of the function at
|
b3 |
a numeric parameter related to the scale the |
a numeric vector of the same length as input. It is the value of
the expression Asym*exp(-b2*b3^x). If all of
the arguments Asym, b2, and b3 are
names of objects the gradient matrix with respect to these names is attached as
an attribute named gradient.
Douglas Bates
nls, selfStart
DNase.1 <- subset(DNase, Run == 1)
SSgompertz(log(DNase.1$conc), 4.5, 2.3, 0.7) # response only
local({ Asym <- 4.5; b2 <- 2.3; b3 <- 0.7
SSgompertz(log(DNase.1$conc), Asym, b2, b3) # response _and_ gradient
})
print(getInitial(density ~ SSgompertz(log(conc), Asym, b2, b3),
data = DNase.1), digits = 5)
## Initial values are in fact the converged values
fm1 <- nls(density ~ SSgompertz(log(conc), Asym, b2, b3),
data = DNase.1)
summary(fm1)
plot(density ~ log(conc), DNase.1, # xlim = c(0, 21),
main = "SSgompertz() fit to DNase.1")
ux <- par("usr")[1:2]; x <- seq(ux[1], ux[2], length.out=250)
lines(x, do.call(SSgompertz, c(list(x=x), coef(fm1))), col = "red", lwd=2)
As <- coef(fm1)[["Asym"]]; abline(v = 0, h = 0, lty = 3)
axis(2, at= exp(-coef(fm1)[["b2"]]), quote(e^{-b[2]}), las=1, pos=0)
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