SSfpl
SelfStarting Nls FourParameter Logistic Model
This selfStart
model evaluates the fourparameter logistic
function and its gradient. It has an initial
attribute that
will evaluate initial estimates of the parameters A
, B
,
xmid
, and scal
for a given set of data.
 Keywords
 models
Usage
SSfpl(input, A, B, xmid, scal)
Arguments
 input
 a numeric vector of values at which to evaluate the model.
 A
 a numeric parameter representing the horizontal asymptote on
the left side (very small values of
input
).  B
 a numeric parameter representing the horizontal asymptote on
the right side (very large values of
input
).  xmid
 a numeric parameter representing the
input
value at the inflection point of the curve. The value ofSSfpl
will be midway betweenA
andB
atxmid
.  scal
 a numeric scale parameter on the
input
axis.
Value

a numeric vector of the same length as
input
. It is the value of
the expression A+(BA)/(1+exp((xmidinput)/scal))
. If all of
the arguments A
, B
, xmid
, and scal
are
names of objects, the gradient matrix with respect to these names is
attached as an attribute named gradient
.
See Also
Examples
library(stats)
Chick.1 < ChickWeight[ChickWeight$Chick == 1, ]
SSfpl(Chick.1$Time, 13, 368, 14, 6) # response only
A < 13; B < 368; xmid < 14; scal < 6
SSfpl(Chick.1$Time, A, B, xmid, scal) # response and gradient
print(getInitial(weight ~ SSfpl(Time, A, B, xmid, scal), data = Chick.1),
digits = 5)
## Initial values are in fact the converged values
fm1 < nls(weight ~ SSfpl(Time, A, B, xmid, scal), data = Chick.1)
summary(fm1)
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