fastmail.fm> writes:
> The problem is that fn is not the model to be fitted.
> The model is y = p1*x/(p2
> + x).
Actually, I would say the model is
y_i ~ Normal(p1*x_i/(p2+x_i),sigma^2) ...
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Full_Name: Britton Kerin
Version: docs on web
OS: linux
Submission from: (NULL) (216.67.49.115)
This section from the introduction to R confused me (reason below):
11.7.1 Least squares
One way to fit a nonlinear model is by minimizing the sum of the squared
errors
(SSE) or residual
