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## [Help-gsl] question for GSL nonlinear least squares fitting

**From**: |
lzhang |

**Subject**: |
[Help-gsl] question for GSL nonlinear least squares fitting |

**Date**: |
Wed, 17 Dec 2014 21:11:56 -0700 |

**User-agent**: |
SquirrelMail/1.4.22 |

Hello,
I'm trying to fit a two dimensional Gaussian function to many measured
data points D(x,y,z) which x and y are position coordinates and z is the
value of point (x,y). However there are some questions about data
dimension.
I use "GSL nonlinear least squares fitting" to do the fitting. The two
dimensional Gaussian G(x,y,p1,p2,...,pn) is matrix which p1,p2,..pn are
parameters. However the f is gsl_vector * datatype in the function int (*
f) (const gsl_vector * x, void * params, gsl_vector * f) of
gsl_multifit_function_fdf. I'm wondering that if the nonlinear least
squares fitting only can deal with one-dimensional data?? If data is
higher dimensional, we need flat the higher-dimensional data into one
dimension?
for two dimensional Gaussian model, the Jacobian is a cube which is (x,y,p).
However If we flat the higher-dimensional data into one dimension, when we
fit the position parameter (x,y ...), Can I get the fitted parameters from
nonlinear least squares fitting directly?
Bests
Li

**[Help-gsl] question for GSL nonlinear least squares fitting**,
*lzhang* **<=**