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Reference Guide
VariableMetricEDMEstimator.cxx
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1// @(#)root/minuit2:$Id$
2// Authors: M. Winkler, F. James, L. Moneta, A. Zsenei 2003-2005
3
4/**********************************************************************
5 * *
6 * Copyright (c) 2005 LCG ROOT Math team, CERN/PH-SFT *
7 * *
8 **********************************************************************/
9
13
14namespace ROOT {
15
16 namespace Minuit2 {
17
18
19double similarity(const LAVector&, const LASymMatrix&);
20
22 // estimate the edm (expected distance to the minimum) = 0.5 * g^T V g (where V is the error matrix, inverse of Hessian)
23 // assuminigfirst derivatives if F are zero at the mminimum,
24
25 if(e.InvHessian().size() == 1)
26 return 0.5*g.Grad()(0)*g.Grad()(0)*e.InvHessian()(0,0);
27
28 double rho = similarity(g.Grad(), e.InvHessian());
29 return 0.5*rho;
30}
31
32 } // namespace Minuit2
33
34} // namespace ROOT
#define g(i)
Definition: RSha256.hxx:105
#define e(i)
Definition: RSha256.hxx:103
MinimumError keeps the inv.
Definition: MinimumError.h:26
double Estimate(const FunctionGradient &, const MinimumError &) const
double similarity(const LAVector &, const LASymMatrix &)
VSD Structures.
Definition: StringConv.hxx:21