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## fitgaussian

version 1.0 (10.3 KB) by

fit a gaussian like curve to data

Updated

FITGAUSS is a function to fit a gaussian like curve "f" to experimental data by Marquardt-Levenberg non-linear least squares minimization. The fitting function has a form of a*exp(-((x-b)/c)^2)+d*x+e. This means the curve is build up a line and a gaussian. INPUTS: "x,y" is input data. "init" is initial guess for parameteres [a b c d e]. If is empty they will be determined automatically from input data and "w" is weight vector (default is ones(size(x))). OUTPUTS: "f" is the values of fitted function. "X" is the estimated parameters. "err" is the normalized error. "it" is number of iterations. "extreme" function from Lic. on Physics Carlos Adrián Vargas Aguilera is used in this function.

Example:
x=1:100;
a=30; b=45; c=10; d=.3; e=20;
f=a*exp(-((x-b)./c).^2)+d*x+e;
fn=f+2*randn(size(f));
[F X]=fitgauss(x,fn);
X=
29.61, 45.20, 10.20, 0.31, 19.18
plot(x,fn,'.',x,F,'r')

pedro silva

the required function frepmat is not provided in the .zip package

Dimitri Shvorob

(Wouldn't the simple Newton's method do for this problem? I have a feeling the task could be done in 2-3 lines with 'fminunc'). FEX visitors should note that what's being fitted is not the normal pdf: consider the 'dx+e' term. The author would do well to use spell-check, provide examples that actually work ('getpts'?), and avoid 'elegant' code like
a_lm=a_est+dp(1);
b_lm=b_est+dp(2);
c_lm=c_est+dp(3);
d_lm=d_est+dp(4);
e_lm=e_est+dp(5);

 13 Jun 2007 Updated description an example
##### MATLAB Release
MATLAB 7.4 (R2007a)