base class for function minimizers; user may give FCN or FCN with Gradient, Parameter starting values and initial Error guess (sigma) (or "step size"), or Parameter starting values and initial covariance matrix; covariance matrix is stored in Upper triangular packed storage format, e.g.
the Elements in the array are arranged like {a(0,0), a(0,1), a(1,1), a(0,2), a(1,2), a(2,2), ...}, the size is nrow*(nrow+1)/2 (see also MnUserCovariance.h);
Definition at line 36 of file FunctionMinimizer.h.
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virtual | ~FunctionMinimizer () |
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virtual FunctionMinimum | Minimize (const FCNBase &, const std::vector< double > &par, const std::vector< double > &err, unsigned int strategy, unsigned int maxfcn, double toler) const =0 |
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virtual FunctionMinimum | Minimize (const FCNGradientBase &, const std::vector< double > &par, const std::vector< double > &err, unsigned int strategy, unsigned int maxfcn, double toler) const =0 |
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virtual FunctionMinimum | Minimize (const FCNBase &, const std::vector< double > &par, unsigned int nrow, const std::vector< double > &cov, unsigned int strategy, unsigned int maxfcn, double toler) const =0 |
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virtual FunctionMinimum | Minimize (const FCNGradientBase &, const std::vector< double > &par, unsigned int nrow, const std::vector< double > &cov, unsigned int strategy, unsigned int maxfcn, double toler) const =0 |
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