Dear all, I have made a study where I needed to manage a histogram which should have a shape which is the result of the superimposition of two distinct gaussians, with similar mean (around 0) and very different constant & sigma values. I managed to realize a macro which performs the fit of two gaussians, which is initialized first excluding the 'signal' events (the higher and narrower one), and fitting the background. Then, I excluded such background and fitted the signal. Finally, using the values obtained from these partial fits, I generated a function which i just the sum of two gaussians, and I refitted it. Of course, the result can be approximative (sometimes I get large chi square). A colleague of mine told me that in PAW there was an automatic procedure to perform a double-gaussian fit. I was wondering if such a procedure is present also in ROOT or not. Another question about fit is the following. We know that in a normalized gaussian there is a precise relationship between the constant and sigma, and then such a function has only two (not three) free parameters. Is there any "automatic" function which performs this? Cheers -- Alberto Pulvirenti, Ph. D. University of Catania / INFN Catania Address: Via S. Sofia, 64 I-95123 Catania Phone: +39-095-378-5286
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