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