I am confused about the use of gsl_multifit_linear capabilities. I already successfully use gsl_fit_linear. I can successfully used gsl_multifit_linear to actually extract the parameters to fit a polynomial model to a dataset. My confusion is how to extract the error estimates of the overall fit. I know (in principle) how to use the covariance matrix to calculate the error estimate myself, but wanted to just use gsl_multifit_linear_est, Which is provided for that purpose.
Unfortunately, I can't make sense of the manual page. int gsl_multifit_linear_est(const <https://www.gnu.org/software/gsl/doc/html/vectors.html#c.gsl_vector> gsl_vector * x, const <https://www.gnu.org/software/gsl/doc/html/vectors.html#c.gsl_vector> gsl_vector * c, const <https://www.gnu.org/software/gsl/doc/html/vectors.html#c.gsl_matrix> gsl_matrix * cov, double * y, double * y_err) This function uses the best-fit multilinear regression coefficients c and their covariance matrix cov to compute the fitted function value y and its standard deviation y_err for the model at the point x. This implies that I should provide some value for "x" (along with the fit coefficients and covariance matrix) to generate the corresponding values for "y" and "y_err". But the function wants me to provide a gsl_vector of x values. Why shouldn't that return a gsl_vector of y and y_err values? I'm confused - anyone able to clarify? Thanks in advance.