R Nonlinear regression

Asked Feb 27 '14 at 15:10

Active Sep 02 '16 at 07:56

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I need a help with a curve fitting problem. I am also quite new to R. I have some data ( 3 pairs of type (x,y)), and need to apply a Nonlinear regression.

Basically, I have a function f(x,a,b,c,d,e,f) - x and 6 other parameters. I want to find a set of (a,b,c,d,e,f) which minimizes weighted sum of squared residuals (weights inversely proportional to squared standard deviations (though in other line it says inversely proportional to variances - maybe it is the same, don't know)).

Can this be done in a simple way on R? Or is there any other software which can do this in a simple manner?

edited Sep 02 '16 at 07:56

Zheyuan Li

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asked Feb 27 '14 at 15:10

Vaidotas

Use the `nls` to do LS iterative fitting for non-linear functions. – Martin Dinov Feb 27 '14 at 15:14
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If you have only three data points it is impossible to fit a six-parameter function. – Roland Feb 27 '14 at 15:15
I know that 3 is very little data as the answer is not likely to be unique. But I have to at least try something : ) – Vaidotas Feb 27 '14 at 15:23
You can try all you want, but it's mathematically impossible. – Roland Feb 27 '14 at 15:31

R Nonlinear regression

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