ROOT Statistics Classes

Calculate the CL upper limit using the Feldman-Cousins method as described in PRD V57 #7, p3873-3889
Fits MC fractions to data histogram (a la HMCMLL, R. Barlow and C. Beeston, Comp. Phys. Comm. 77 (1993) 219-228). Takes into account both data and Monte Carlo statistical uncertainties through a likelihood fit using Poisson statistics; however, the template (MC) predictions are also varied within statistics, leading to additional contributions to the overall likelihood. This leads to many more fit parameters (one per bin per template), but the minimisation with respect to these additional parameters is done analytically rather than introducing them as formal fit parameters. Some special care needs to be taken in the case of bins with zero content.
Algorithm to compute 95% C.L. limits using the Likelihood ratio semi-Bayesian method (CLs method; see e.g. T. Junk, NIM A434, p. 435-443, 1999). It takes signal, background and data histograms wrapped in a TLimitDataSource as input and runs a set of Monte Carlo experiments in order to compute the limits. If needed, inputs are fluctuated according to systematics.
General minimisation
Multi-dim parametrisation and fitting
A Neural Network class
Principal Component Analysis
Computes confidence intervals for the rate of a Poisson in the presence of background and efficiency with a fully frequentist treatment of the uncertainties in the efficiency and background estimate using the profile likelihood method. The signal is always assumed to be Poisson; background may be Poission, Gaussian, or user-supplied; efficiency may be Binomial, Gaussian, or user-supplied. See publication at Nucl.Instrum.Meth.A551:493-503,2005.
1- and 2-dim background estimation, smoothing, deconvolution, peak search and fitting, and orthogonal transformations
You can also look at:
TH1 base class for the histograming package
TTree general ntuple manipulation and analysis system
TMatrixDBase Linear algebra package
TMath small utility algorithms.

Last update: 25-Nov-2004 by Ilka Antcheva