2019-07-08 17:32:18 +02:00
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#![cfg_attr(feature = "cargo-clippy", allow(clippy::float_cmp, map_clone))]
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2017-05-30 10:54:14 +02:00
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2019-07-08 16:01:13 +02:00
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use rand_distr::Distribution;
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2018-07-06 10:31:26 +02:00
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2019-07-08 16:17:04 +02:00
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use average::{Kurtosis, Estimate, assert_almost_eq};
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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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2019-07-08 16:01:13 +02:00
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let normal = rand_distr::Normal::new(2.0, 3.0).unwrap();
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2017-05-28 23:46:15 +02:00
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let mut a = Kurtosis::new();
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for _ in 0..1_000_000 {
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2018-07-06 10:31:26 +02:00
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a.add(normal.sample(&mut ::rand::thread_rng()));
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2017-05-28 23:46:15 +02:00
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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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let lambda = 2.0;
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2019-07-08 16:01:13 +02:00
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let normal = rand_distr::Exp::new(lambda).unwrap();
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2017-05-28 23:46:15 +02:00
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let mut a = Kurtosis::new();
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for _ in 0..6_000_000 {
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2018-07-06 10:31:26 +02:00
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a.add(normal.sample(&mut ::rand::thread_rng()));
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2017-05-28 23:46:15 +02:00
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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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2018-03-07 17:57:49 +01:00
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assert_almost_eq!(a.skewness(), 2.0, 1e-1);
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2017-05-28 23:46:15 +02:00
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assert_almost_eq!(a.kurtosis(), 6.0, 1e-1);
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}
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