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Hi Rene and Martin, I think you want the TH1's stored in a TH2 where the the TH1's are a function of the missing mass and the additional dimension of a TH2 is used for the angle . To me it is not clear when using the THStack where the angle info is stored . But besides that detail, the real "meat" is in how to specify the fit function and the objective function (something like H1FitChisquare and H1FitLikelihood) . The descripton/wishlist of Martin is from a statistical point not clear . The only part of the description I understand is that he wants to fit 10 histos simultaneously and that the fit parameters should vary smoothly as a function of the angle : suppose for the 1-dim case your fitting function was : z_fit = b0 + b1 x +b2 x^2 + a0 exp(-a1 (x-a2)^2) where x is the missing mass b0,b1 and b2 the background par and a0,a1 and a2 the parameters for a Gauss now for the 2-dim case : z_fit = b0 + b1 x + b2 x^2 +b3 y + b4 y^2 + b5 xy + a0 exp(-a1 (x-a2)^2) where a0 = d0 + d1 y , a1 = e0 + e1 y , ...... if you assume a linear angle dependence The way you code this up is by using directly minuit as showm in tutorials/Ifit.C Eddy --- Rene Brun <brun@pcbrun.cern.ch> wrote: > 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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