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
.