This
selfStart model evaluates an alternative parameterization
of the asymptotic regression function and the gradient with respect to
those parameters. It has an
initial attribute that creates
initial estimates of the parameters
Asym,
lrc, and
c0
.
USAGE:
SSasympOff(input, Asym, lrc, c0)
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).
lrc
a numeric parameter representing the natural logarithm of
the rate constant.
c0
a numeric parameter representing the
input for which the
response is zero.
VALUE:
a numeric vector of the same length as
input. It is the value of
the expression
Asym*(1 - exp(-exp(lrc)*(input - c0))). If all of
the arguments
Asym,
lrc, and
c0 are names of objects, the
gradient matrix with respect to these names is attached as an
attribute named
gradient.