How to get the error value when fitting a gaussin curve to a data?

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I have the following data fitting curve:
And i'd like to compute the error associated to this fitting, the var error! If some one knows how to do it please help me.
Thanks

Accepted Answer

Star Strider
Star Strider on 5 Jan 2015
To do the plot and get the data to analyse the error of the fit, this works:
x = 0.25*randn(1000,1)+1; % Create Data
h = histfit(x,50);
histdata = get(h(1),'XData'); % Get Histogram Data
redcurve = get(h(2),'YData'); % Get Fit Data
histctrs = mean(histdata); % Mean Of Bin Edges
redcurve2 = mean(reshape(redcurve, 2, [])); % Mean Of Bin Edges Fit
fit_err = histctrs - redcurve2; % Error
SSE = sum(fit_err.^2); % Sum-Squared Error
MSE = mean(fit_err.^2); % Mean-Squared-Error
RMSE = sqrt(MSE); % Root-Mean-Squared-Error
Your data actually seem to me to be lognormally distributed, so consider using the 'lognormal' distribution option.

More Answers (2)

Joao Costa
Joao Costa on 5 Jan 2015
But how do I get the red line (gaussian curve) In my code I did this:
histfit(data);
Thank you

Joao Costa
Joao Costa on 7 Jan 2015
Thanks a lot star strider! I only had to normalize the vector!

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