34. Least-Squares Fitting

This chapter describes routines for performing least squares fits to experimental data using linear combinations of functions. The data may be weighted or unweighted. For weighted data the functions compute the best fit parameters and their associated covariance matrix. For unweighted data the covariance matrix is estimated from the scatter of the points, giving a variance-covariance matrix. The functions are divided into separate versions for simple one- or two-parameter regression and multiple-parameter fits. The functions are declared in the header file `gsl_fit.h'

34.1 Linear regression
34.2 Linear fitting without a constant term
34.3 Multi-parameter fitting
34.4 Examples
34.5 References and Further Reading