Function rgsl::fit::linear

pub fn linear(x: &[f64], xstride: usize, y: &[f64], ystride: usize, n: usize, c0: &mut f64, c1: &mut f64, cov00: &mut f64, cov01: &mut f64, cov11: &mut f64, sumsq: f64) -> Value

This function computes the best-fit linear regression coefficients (c0,c1) of the model Y = c_0 + c_1 X for the dataset (x, y), two vectors of length n with strides xstride and ystride. The errors on y are assumed unknown so the variance-covariance matrix for the parameters (c0, c1) is estimated from the scatter of the points around the best-fit line and returned via the parameters (cov00, cov01, cov11). The sum of squares of the residuals from the best-fit line is returned in sumsq. Note: the correlation coefficient of the data can be computed using gsl_stats_correlation (see Correlation), it does not depend on the fit.