Online algorithm for mean and std dev

[genos]

First off, thank you for this library! I've been investigating various hyperparameter importance routines, and I wanted to delve deeper into fANOVA; having a Rust implementation to look through is really nice.

I do have one small suggestion: the functions functions::mean and functions::mean_and_stddev could be updated to use Welford's online algorithm, computing the mean and standard deviation in a single pass. This would also remove the need for Clone:

pub fn mean(xs: impl Iterator<Item = f64>) -> f64 {
    mean_and_stddev(xs).0
}

pub fn mean_and_stddev(xs: impl Iterator<Item = f64>) -> (f64, f64) {
    let (mut mean, mut s, mut n) = (0.0, 0.0, 0.0);
    for x in xs {
        n += 1.0;
        let delta = x - mean;
        mean += delta / n;
        s += delta * (x - mean);
    }
    assert!(n >= 2.0, "Need more than 2 values for standard deviation");
    (mean, (s / (n - 1.0)).sqrt())
}

This also uses Bessel's correction for unbiased sample standard deviation (n - 1 instead of n).

Feel free to ignore my suggestion, and thanks again for this library!

Edit: I made some errors in my code suggestions (copy-pasting from another project). Fixed now!

[sile]

Thank your for reaching out.
Your suggestion sounds nice to me. So, let me consider that deeper this or next weekend.
BTW, if you're interested in creating a PR to reflect the suggestion, it is, of course, very welcomed.

[genos]

Thanks for your response! I've put up PR #3 to address/suggest what I put here, plus some other general housekeeping (update tests so they still pass, get cargo clippy to be quiet). Thanks again for your time and your great project.

[sile]

Addressed by #3