> data <- data.frame(x=c(1:5), y=c(1,3,2,NA,4))
> nls(y ~ A*x^2 +sqrt(0.08*A)*x, data=data, start=list(A=0))
Nonlinear regression model
model: y ~ A * x^2 + sqrt(0.08 * A) * x
data: data
A
0.1577584
residual sum-of-squares: 5.445525
>At Thursday 07:54 PM 11/13/2003 +0100, JB wrote:
At 13.11.2003 (17:17), Roger D. Peng wrote:You could use nls() or optimize().
-roger
Well, thx. This is very complicated. In Mupad I simply say:
r:=stats::reg(t_list,x_list,a/2*t^2+sqrt(0.08*a)*t,[t],[a])
and get the (right) answer. How would the same command in R go?
TIA,
jb
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