Iterative reweighted least squares
IterativeReweightedLS ( int n , LinearForward * p , Vector <double>* data, int lp, int w_nit, int nit, double tape, double tol , int verb) a constructor
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IterativeReweightedLS (int n , LinearForward * p , Vector <double>* data, int lp, int w_nit, int nit, double tape, double tol ) a constructor | |||||||||||||||||||
Model <double> | optimizer ( Model <double>& m0) IRLS search starting from m0, returns an optimum model | ||||||||||||||||||
Model <long> | optimizer ( Model <long>& m0) IRLS search starting from m0, returns an optimum model |
This algorithm gives you the flexibility to choose different norms (other than the norm 2) to solve linear systems. A comprehensible description of this method can be found in "Robust methods in inverse theory", 1988, Inverse Problems 4, by J. Scales and A. Gersztenkorn.This procedure is not fully tested at the current stage.
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