kernel_density_estimation/kernel/
silverman.rs

1//! Silverman kernel function.
2
3use crate::float::{float, primitive, KDEFloat};
4use crate::kernel::Kernel;
5
6use std::f64::consts::{E, FRAC_PI_4, SQRT_2};
7
8/// Silverman kernel function.
9#[derive(Clone, Copy, Debug)]
10pub struct SilvermanKernel;
11
12impl<F: KDEFloat> Kernel<F> for SilvermanKernel {
13    fn pdf(&self, x: F) -> F {
14        let abs_x = x.abs();
15        if abs_x <= F::one() {
16            let term_a = 0.5 * E.powf(-primitive!(x.abs()) / SQRT_2);
17            let term_b = ((primitive!(x.abs()) / SQRT_2) + FRAC_PI_4).sin();
18            float!(term_a * term_b)
19        } else {
20            F::zero()
21        }
22    }
23}
24
25#[cfg(test)]
26mod tests {
27    use super::SilvermanKernel;
28    use crate::kernel::Kernel;
29    use approx::*;
30
31    #[test]
32    fn silverman_kernel() {
33        let kernel = SilvermanKernel;
34
35        let x = 0.0;
36        let res = kernel.pdf(x);
37        assert_relative_eq!(res, 0.35355, epsilon = 1.0e-5);
38
39        let x = -1.0;
40        let res = kernel.pdf(x);
41        assert_relative_eq!(res, 0.24578, epsilon = 1.0e-5);
42
43        let x = 1.0;
44        let res = kernel.pdf(x);
45        assert_relative_eq!(res, 0.24578, epsilon = 1.0e-5);
46
47        let x = 0.5;
48        let res = kernel.pdf(x);
49        assert_relative_eq!(res, 0.31886, epsilon = 1.0e-5);
50    }
51}
kernel_density_estimation/kernel/silverman.rs

kernel_density_estimation/kernel/
silverman.rs
