Hi list,
I have a little curve fitting problem.
I would like to fit a sigmoid curve to my data using the following equation:
f(x) = 1/(1 + exp(-(x-c)*b)) (or any other form for that matter)
Where x is the distance/location within the dataframe, c is the shift of the
curve across the dataframe and b is the steepness of the curve.
I've been playing with glm() and glm.fit() but without any luck.
for example the most simple example
x = -10:10
y = 1/(1 + exp(-x))
glm(y ~ x, family=binomial(link="logit"))
I get a warning:
non-integer #successes in a binomial glm! in: eval(expr, envir, enclos)
and some erratic results
This is the most simple test to see if I could fit a curve to this perfect data
so since this didn't work out, bringing in the extra parameters is a whole
other ballgame so could someone give me a clue?
Kind regards,
Koen
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