Hi Martin, A possible solution could be via THStack and implement THStack::Fit. A THStack is a list of histograms. The existing fitting algorithms (H1FitChisquare and H1FitLikelihood) could be extended to support a THStack. If somebody has a better idea, let me know. Rene Brun On Sat, 6 Nov 2004, schulte-wissermann wrote: > hi all ROOTers, > consider the following problem: > - you have a signal (e.g. missing-mass-spektrum) which is > parameterized by a Lorentz convoluted with a Gaus. > the signal is on some kind of background wich you emulate by a > cubic function. after the fit i get as a result (let's say) seven > parameters. > > NO PROBLEM SOFAR: see the famous FittingDemo and langaus tutorials. > > now the problem: > i now split my data considering another observable (let's say ten > missing-mass distributions as a function of an angle of an ejectile). > i now have to fit ten INDIVIDUAL histos, however physics tells me > that the fits are correlated: > - the parameters should be 'some' smooth function of the additional observable. > - the probability of the fits should be 'some' smooth function of the additional observable. > - the sum of all signals should match the integral of the total signal. > > now the question: > how can i simultaniously fit the ten histos? is there a ROOT-class? > are there some examples? one could think of some > multi-constraint, iterative fitting method; or one could try to > fit the surface of a TH2F filled with > h->Fill(missingmass, angle, totalcountsofthisbin). > i'm currently working on this problem, but the output is not yet what i'm aiming for. > > thanx in advance, > martin >
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