.\" -*- nroff -*- generated from .Rd format
.BG
.FN SSasymp
.TL
Asymptotic regression model
.DN
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.
.CS
SSasymp(input, Asym, R0, lrc)
.RA
.AG input
a numeric vector of values at which to evaluate the model
.AG Asym
a numeric parameter representing the horizontal asymptote on
the right side (very large values of `input')
.AG R0
a numeric parameter representing the response when
`input' is zero.
.AG lrc
a numeric parameter representing the natural logarithm of
the rate constant
.RT
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'.
.SA
`nls', `selfStart'
.EX
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
.KW models
.WR
