average 0.6.0

#[macro_use] extern crate average;

extern crate rand;

use average::Kurtosis;

#[test]
fn normal_distribution() {
    use rand::distributions::{Normal, IndependentSample};
    let normal = Normal::new(2.0, 3.0);
    let mut a = Kurtosis::new();
    for _ in 0..1_000_000 {
        a.add(normal.ind_sample(&mut ::rand::thread_rng()));
    }
    assert_almost_eq!(a.mean(), 2.0, 1e-2);
    assert_almost_eq!(a.sample_variance().sqrt(), 3.0, 1e-2);
    assert_almost_eq!(a.population_variance().sqrt(), 3.0, 1e-2);
    assert_almost_eq!(a.error_mean(), 0.0, 1e-2);
    assert_almost_eq!(a.skewness(), 0.0, 1e-2);
    assert_almost_eq!(a.kurtosis(), 0.0, 4e-2);
}

#[test]
fn exponential_distribution() {
    use rand::distributions::{Exp, IndependentSample};
    let lambda = 2.0;
    let normal = Exp::new(lambda);
    let mut a = Kurtosis::new();
    for _ in 0..6_000_000 {
        a.add(normal.ind_sample(&mut ::rand::thread_rng()));
    }
    assert_almost_eq!(a.mean(), 1./lambda, 1e-2);
    assert_almost_eq!(a.sample_variance().sqrt(), 1./lambda, 1e-2);
    assert_almost_eq!(a.population_variance().sqrt(), 1./lambda, 1e-2);
    assert_almost_eq!(a.error_mean(), 0.0, 1e-2);
    assert_almost_eq!(a.skewness(), 2.0, 1e-2);
    assert_almost_eq!(a.kurtosis(), 6.0, 1e-1);
}