Hello,
The fit works with the following:
//xm;ym
d = [
2.0 99.9449173761
1.0 99.8097145719
0.5 97.9769654482
0.25 36.4046069104
0.1 1.4872308463
0.071 0.5207811718
0.063 0.3705558338
];
xm = d(:,1);
ym = d(:,2);
//Script used to fit data
miny = min(ym);
maxy = max(ym);
minx = min(xm);
maxx = max(xm);
//Function describing problem (I want to find best fit by finding n()).
function g1=f1(x,n)
g1 = miny + ((maxy-miny)./ ..
( (1 + (n(1)*(x/n(2)).^n(3)) + (1-n(1))*((x/n(2)).^n(4)))).^n(5))
endfunction
function e=G(n,z)
e = abs(z(2) - f1(z(1),n)) // Note here that we take the modulus
endfunction
n0 = [1 ; 1; 1; 1; 1];
Zz = [xm.' ; ym.'];
[n0_opt,err] = datafit(G, Zz, n0)
clf
plot2d("ll", xm,ym);
c = e.children(1)
c.line_mode = "off";
c.mark_mode = "on";
c.mark_size_unit = "point";
c.mark_size = 4;
plot2d(xm,f1(xm,n0_opt))
We get:
-->[n0_opt,err] = datafit(G, Zz, n0)
err =
0.0485009
n0_opt =
0.9641563
0.3183242
- 7.833407
- 2.3794352
0.5056993
// + Figure
Not so bad.
Regards
Samuel
Le 17/12/2014 21:14, Maihem a écrit :
Thanks for answer but it seems that implementation of this only allowed to
avoid error cause calculated parameters still don't fit to data.
Parameters calculated by implementation real on e gives fit parameters:
n(1)= 1.264264
n(2)= - 0.1891816
n(3)= 1.6592188
n(4)= 0.9977104
n(5)= 1.0404815
but this parameters are wrong.
For example I fitted this equation using Gnuplot and I recived:
n(1)= 0.960002
n(2)= 0.331008
n(3)= -8.26945
n(4)= -1.9777
n(5)= 0.423854
and this results from gnuplot fits this function to data
I'm little confused why I can't receive similar solution from scilab
Łukasz
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