Asymptotic regression model

DESCRIPTION:

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.

USAGE:

SSasymp(input, Asym, R0, lrc) 

REQUIRED 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)
R0
a numeric parameter representing the response when input is zero.
lrc
a numeric parameter representing the natural logarithm of the rate constant

VALUE:

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 .

SEE ALSO:

,

EXAMPLES:

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