TMVA::MethodBase

 default destructur

 options parser

 default initialisation called by all constructors

 define the options (their key words) that can be set in the option string 
 here the options valid for ALL MVA methods are declared.
 know options: Preprocess=None,Decorrelated,PCA  to use decorrelated variables 
                                                 instead of the original ones
               PreprocessType=Signal,Background  which decorrelation matrix to use
                                                 in the method. Only the Likelihood
                                                 Method can make proper use of independent
                                                 transformations of signal and background
               V  for Verbose output (!V) for non verbos
               H  for Help 

 the option string is decoded, for availabel options see "DeclareOptions"

 all histograms should be created in the method's subdirectory

 general method used in writing the header of the weight files where
 the used variables, preprocessing type etc. is specified

 Function to write options and weights to file

 Function to write options and weights to file

 read the header from the weight files of the different MVA methods

 return the normalized event variable (normalized to interval [0,1]

 returns the ROOT directory where info/histograms etc of the 
 corresponding MVA method are stored

 set the weight file name (depreciated)

 retrieve weight file name

 tree sanity checks

 set directory of weight file

 renormalises variable with respect to its min and max

 renormalises variable with respect to its min and max

 initialisation of MVA testing 

 prepare tree branch with the method's discriminating variable

 test the method - not much is done here... mainly furthor initialisation

 fill background efficiency (resp. rejection) versus signal efficiency plots
 returns signal efficiency at background efficiency indicated in theString

 fill background efficiency (resp. rejection) versus signal efficiency plots
 returns signal efficiency at background efficiency indicated in theString

 compute significance of mean difference
 significance = |<S> - <B>|/Sqrt(RMS_S2 + RMS_B2)

 compute "separation" defined as
 <s2> = (1/2) Int_-oo..+oo { (S(x)2 - B(x)2)/(S(x) + B(x)) dx }

 plot significance, S/Sqrt(S^2 + B^2), curve for given number 
 of signal and background events; returns cut for optimal significance
 also returned via reference is the optimal significance 

 computes Mu-transform
---------------------------------------------------------------------------------------
 Authors     : Francois Le Diberder and Muriel Pivk
 Reference   : Muriel Pivk,
               "Etude de la violation de CP dans la désintégration
                B0 -> h+ h- (h = pi, K) auprès du détecteur BaBar à SLAC",
               PhD thesis at Universite de Paris VI-VII, LPNHE (IN2P3/CNRS), Paris, 2003
               http://tel.ccsd.cnrs.fr/documents/archives0/00/00/29/91/index_fr.html

 Definitions : Bhat = PDFbackground(x)/(PDFbackground(x) + PDFsignal(x))
               mu   = mu(b) = Int_0B Bhat[b'] db'
---------------------------------------------------------------------------------------

 calculates rms,mean, xmin, xmax of the event variable
 this can be either done for the variables as they are or for
 normalised variables (in the range of 0-1) if "norm" is set to kTRUE

 writes all MVA evaluation histograms to file

 interface for RootFinder

 returns efficiency as function of cut

 prints out the options set in the options string and the defaults

 write options to output stream (e.g. in writing the MVA weight files

 read option back from the weight file

 write special monitoring histograms to file - not implemented for this method

 the new way to get the MVA value

 normalisation accessors

 static pointer to this object

 reset required for RootFinder

 sets the minimum requirement on the MVA output to declare an event 
 signal-like

 TestVar (the variable name used for the MVA)

 MVA prefix (e.g., "TMVA_")