| SSasymp {stats} | R Documentation |
This selfStart model evaluates the asymptotic regression
function and its gradient. It has an initial attribute that
will evaluate initial estimates of the parameters Asym, R0,
and lrc for a given set of data.
SSasymp(input, Asym, R0, lrc)
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). |
R0 |
a numeric parameter representing the response when
input is zero. |
lrc |
a numeric parameter representing the natural logarithm of the rate constant. |
a numeric vector of the same length as input. It is the value of
the expression Asym+(R0-Asym)*exp(-exp(lrc)*input). If all of
the arguments Asym, R0, and lrc are
names of objects, the gradient matrix with respect to these names is
attached as an attribute named gradient.
Jose Pinheiro and Douglas Bates
Lob.329 <- Loblolly[ Loblolly$Seed == "329", ] SSasymp( Lob.329$age, 100, -8.5, -3.2 ) # response only Asym <- 100 resp0 <- -8.5 lrc <- -3.2 SSasymp( Lob.329$age, Asym, resp0, lrc ) # response and gradient getInitial(height ~ SSasymp( age, Asym, resp0, lrc), data = Lob.329) ## Initial values are in fact the converged values fm1 <- nls(height ~ SSasymp( age, Asym, resp0, lrc), data = Lob.329) summary(fm1)