Re: root : unbinned fit 1D

There was a typo:  

         s**2 ~ s_f**2 = 1/N Sum_i (x_i - c_f)**2

Elemer

On Sun, 6 Dec 2009, Elemer Nagy wrote:

Hi Marc,

assuming that each of the N data points x_i is independent: construct a likelihood L as a product of Gaussians from the datapoints and apply MINUIT to determine the Gaussian central value, c and (if needed) its sigma, s. It is more easy if you take the logarithm of the likelihood, in this case you deal with the sum of data:

• log L = Sum_i [(x_i-c)/s]**2/2 + N ln s

Even w/o MINUIT you can solve the fit equations:

     dL/dc = dL/ds = 0

which gives you (of course):

     c ~ c_f = 1/N Sum_i x_i
and

     s ~ s_f = 1/N Sum_i (x_i - c_f)**2

Elemer

On Sun, 6 Dec 2009, Marc Escalier wrote:

Dear root experts,

would somebody know how to proceed to do a unbinned fit of a TH1 histo ?

for example, lets consider
MyTH1Histo->Fit("gaus")

==>i wish to do this fit, but with a unbinned fit

thank you

(i will thank those who know in private to prevent spamming people)

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