2017-05-30 10:54:14 +02:00
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#![cfg_attr(feature = "cargo-clippy", allow(float_cmp, map_clone))]
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2017-05-28 23:46:15 +02:00
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#[macro_use] extern crate average;
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extern crate rand;
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2017-06-25 14:39:23 +02:00
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use average::{Kurtosis, Estimate};
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2017-05-28 23:46:15 +02:00
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#[test]
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fn normal_distribution() {
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use rand::distributions::{Normal, IndependentSample};
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let normal = Normal::new(2.0, 3.0);
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let mut a = Kurtosis::new();
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for _ in 0..1_000_000 {
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a.add(normal.ind_sample(&mut ::rand::thread_rng()));
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}
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assert_almost_eq!(a.mean(), 2.0, 1e-2);
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assert_almost_eq!(a.sample_variance().sqrt(), 3.0, 1e-2);
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assert_almost_eq!(a.population_variance().sqrt(), 3.0, 1e-2);
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assert_almost_eq!(a.error_mean(), 0.0, 1e-2);
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assert_almost_eq!(a.skewness(), 0.0, 1e-2);
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assert_almost_eq!(a.kurtosis(), 0.0, 4e-2);
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}
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#[test]
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fn exponential_distribution() {
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use rand::distributions::{Exp, IndependentSample};
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let lambda = 2.0;
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let normal = Exp::new(lambda);
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let mut a = Kurtosis::new();
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for _ in 0..6_000_000 {
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a.add(normal.ind_sample(&mut ::rand::thread_rng()));
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}
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assert_almost_eq!(a.mean(), 1./lambda, 1e-2);
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assert_almost_eq!(a.sample_variance().sqrt(), 1./lambda, 1e-2);
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assert_almost_eq!(a.population_variance().sqrt(), 1./lambda, 1e-2);
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assert_almost_eq!(a.error_mean(), 0.0, 1e-2);
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assert_almost_eq!(a.skewness(), 2.0, 1e-2);
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assert_almost_eq!(a.kurtosis(), 6.0, 1e-1);
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}
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