template<class HistT>
| double Impala::Core::Histogram::FitWeibullMarginal< HistT >::GammaEst | ( | double | gamma | ) | [inline, private] |
Definition at line 234 of file FitWeibullMarginal.h.
References Impala::Core::Histogram::FitWeibullMarginal< HistT >::BetaEst(), Impala::Core::Histogram::FitWeibullMarginal< HistT >::DiGamma(), Impala::Core::Histogram::FitWeibullMarginal< HistT >::mBeta, Impala::Core::Histogram::FitWeibullMarginal< HistT >::mBins, Impala::Core::Histogram::FitWeibullMarginal< HistT >::mDx, Impala::Core::Histogram::FitWeibullMarginal< HistT >::mHist, Impala::Core::Histogram::FitWeibullMarginal< HistT >::mNorm, and Impala::Core::Histogram::FitWeibullMarginal< HistT >::mPrecision.
Referenced by Impala::Core::Histogram::FitWeibullMarginal< HistT >::DoFit().
00235 { 00236 double sum = 0; 00237 00238 mBeta = BetaEst(gamma); 00239 00240 double ddx = mDx/mBeta; 00241 double x = mDx/mBeta; 00242 00243 for (int i=0; i<mBins; i++, x += ddx) 00244 if (mHist[i] > mPrecision) 00245 sum += pow(x, gamma)*(1.0-gamma*log(x))*mHist[i]; 00246 00247 return -(sum/mNorm+gamma-1.0+log(gamma)+DiGamma(1./gamma)); 00248 }
Here is the call graph for this function:
