class RooStats::MCMCInterval: public RooStats::ConfInterval

 default constructor

 constructor from parameter of interest and Markov chain object

 determine whether this point is in the confidence interval

 set the desired confidence level (see GetActualConfidenceLevel())
 Note: calling this function triggers the algorithm that determines
 the interval, so call this after initializing all other aspects
 of this IntervalCalculator
 Also, calling this function again with a different confidence level
 retriggers the calculation of the interval

 get the desired confidence level (see GetActualConfidenceLevel())

 return a set containing the parameters of this interval
 the caller owns the returned RooArgSet*

 get the cutoff bin height for being considered in the
 confidence interval

 get the cutoff RooNDKeysPdf value for being considered in the
 confidence interval

virtual Double_t GetKeysPdfCutoff() { return fKeysCutoff; }
 get the actual value of the confidence level for this interval.

 whether the specified confidence level is a floor for the actual
 confidence level (strict), or a ceiling (not strict)

 check if parameters are correct. (dummy implementation to start)

 Set the parameters of interest for this interval
 and change other internal data members accordingly

 Set the MarkovChain that this interval is based on

 Set which parameters go on which axis.  The first list element
 goes on the x axis, second (if it exists) on y, third (if it
 exists) on z, etc

 return a list of RooRealVars representing the axes
 you own the returned RooArgList

 get the lowest value of param that is within the confidence interval

 determine lower limit of the lower confidence interval

 get the lower limit of param in the shortest confidence interval
 Note that this works better for some distributions (ones with exactly
 one maximum) than others, and sometimes has little value.

 determine lower limit in the shortest interval by using keys pdf

 determine lower limit using histogram

 determine lower limit using histogram

 determine lower limit using histogram

 get the highest value of param that is within the confidence interval

 determine upper limit of the lower confidence interval

 get the upper limit of param in the confidence interval
 Note that this works better for some distributions (ones with exactly
 one maximum) than others, and sometimes has little value.

 determine upper limit in the shortest interval by using keys pdf

 determine upper limit using histogram

 determine upper limit using histogram

 determine upper limit using histogram

 Determine the approximate maximum value of the Keys PDF

 set the number of steps in the chain to discard as burn-in,
 starting from the first

 set whether to use kernel estimation to determine the interval

 set whether to use a sparse histogram.  you MUST also call
 SetUseKeys(kFALSE) to use a histogram.

 get whether we used kernel estimation to determine the interval

 get the number of steps in the chain to disard as burn-in,
 get the number of steps in the chain to disard as burn-in,
 starting from the first

 set the number of bins to use (same for all axes, for now)
virtual void SetNumBins(Int_t numBins);
 Get a clone of the histogram of the posterior

 Get a clone of the keys pdf of the posterior

 Get a clone of the (keyspdf * heaviside) product of the posterior

 Get the number of parameters of interest in this interval

 Get the markov chain on which this interval is based
 You do not own the returned MarkovChain*

 Get a clone of the markov chain on which this interval is based
 as a RooDataSet.  You own the returned RooDataSet*

 Get the markov chain on which this interval is based
 as a RooDataSet.  You do not own the returned RooDataSet*

 Get a clone of the markov chain on which this interval is based
 as a RooDataHist.  You own the returned RooDataHist*

 Get a clone of the markov chain on which this interval is based
 as a THnSparse.  You own the returned THnSparse*

 Get a clone of the NLL variable from the markov chain

 Get a clone of the weight variable from the markov chain

 set the acceptable level or error for Keys interval determination

 Set the type of interval to find.  This will only have an effect for
 1-D intervals.  If is more than 1 parameter of interest, then a
 "shortest" interval will always be used, since it generalizes directly
 to N dimensions

 Return the type of this interval

 set the left-side tail fraction for a tail-fraction interval

 kbelasco: The inner-workings of the class really should not be exposed
 like this in a comment, but it seems to be the only way to give
 the user any control over this process, if they desire it

 Set the fraction delta such that
 topCutoff (a) is considered == bottomCutoff (b) iff
 (TMath::Abs(a - b) < TMath::Abs(fDelta * (a + b)/2))
 when determining the confidence interval by Keys

 functions