Asymptotic Regression Model
Usage
SSasymp(input, Asym, R0, lrc)
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.
|
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.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, as opposed to expressions or explicit numerical
values, the gradient matrix with respect to these names is attached as
an attribute named gradient
.Author(s)
Jose Pinheiro and Douglas BatesSee Also
nls
, selfStart
Examples
library( lme )
data( Loblolly )
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