selfStart model evaluates the logistic
function and its gradient. It has an
initial attribute that
creates initial estimates of the parameters
scal. In R 3.4.2 and earlier, that
init function failed when
min(input) was exactly zero.
SSlogis(input, Asym, xmid, scal)
a numeric vector of values at which to evaluate the model.
a numeric parameter representing the asymptote.
a numeric parameter representing the
a numeric scale parameter on the
a numeric vector of the same length as
input. It is the value of
Asym/(1+exp((xmid-input)/scal)). If all of
names of objects the gradient matrix with respect to these names is attached as
an attribute named
José Pinheiro and Douglas Bates
1 2 3 4 5 6 7 8
Chick.1 <- ChickWeight[ChickWeight$Chick == 1, ] SSlogis(Chick.1$Time, 368, 14, 6) # response only Asym <- 368; xmid <- 14; scal <- 6 SSlogis(Chick.1$Time, Asym, xmid, scal) # response and gradient getInitial(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1) ## Initial values are in fact the converged values fm1 <- nls(weight ~ SSlogis(Time, Asym, xmid, scal), data = Chick.1) summary(fm1)
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