mathru/statistics/distrib/
bernoulli.rs

1//! Bernoulli Distribution
2use crate::{algebra::abstr::Real, statistics::distrib::Discrete};
3#[cfg(feature = "serde")]
4use serde::{Deserialize, Serialize};
5use std::clone::Clone;
6
7/// Bernoulli distribution
8///
9/// Fore more information:
10///
11/// <https://en.wikipedia.org/wiki/Bernoulli_distribution>
12#[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
13#[derive(Clone, Copy, Debug)]
14pub struct Bernoulli<T> {
15    p: T,
16}
17
18impl<T> Bernoulli<T>
19where
20    T: Real,
21{
22    /// Create a probability distribution with p(X=1) = p
23    ///
24    /// # Arguments
25    ///
26    /// * `p` Probability that random varibale X=1, 0.0 <= p <= 1.0
27    ///
28    /// # Panics
29    ///
30    /// if p < 0 || p > 1.0
31    ///
32    /// # Example
33    ///
34    /// ```
35    /// use mathru::statistics::distrib::Bernoulli;
36    ///
37    /// let distrib: Bernoulli<f64> = Bernoulli::new(0.2);
38    /// ```
39    pub fn new(p: T) -> Bernoulli<T> {
40        if p < T::zero() || p > T::one() {
41            panic!()
42        }
43
44        Bernoulli { p }
45    }
46}
47
48impl<T> Discrete<T, u8, T> for Bernoulli<T>
49where
50    T: Real,
51{
52    /// Probability mass function of the Bernoulli distribution
53    ///
54    ///
55    /// # Arguments
56    ///
57    /// * `x` Random variable x &isin; {0, 1}
58    ///
59    /// # Panics
60    ///
61    /// if x &notin; {0, 1}
62    /// # Example
63    ///
64    /// ```
65    /// use mathru::statistics::distrib::{Bernoulli, Discrete};
66    ///
67    /// let distrib: Bernoulli<f64> = Bernoulli::new(0.2);
68    /// let x: u8 = 0;
69    /// let p: f64 = distrib.pmf(x);
70    /// ```
71    fn pmf(&self, x: u8) -> T {
72        if (x == 1) || (x == 0) {
73            if x == 0 {
74                T::one() - self.p
75            } else {
76                self.p
77            }
78        } else {
79            panic!()
80        }
81    }
82
83    /// Cumulative distribution function of the Bernoulli distribution
84    ///
85    /// # Arguments
86    ///
87    /// * `x` Random variable x &isin; {0, 1}
88    ///
89    /// # Example
90    ///
91    /// ```
92    /// use mathru::statistics::distrib::{Bernoulli, Discrete};
93    ///
94    /// let distrib: Bernoulli<f64> = Bernoulli::new(0.2);
95    /// let x: f64 = 0.4;
96    /// let p: f64 = distrib.cdf(x);
97    /// ```
98    fn cdf(&self, x: T) -> T {
99        if x >= T::one() {
100            return T::one();
101        }
102
103        if x <= T::zero() {
104            T::zero()
105        } else {
106            T::one() - self.p
107        }
108    }
109
110    /// Expected value
111    ///
112    /// # Example
113    ///
114    /// ```
115    /// use mathru::statistics::distrib::{Bernoulli, Discrete};
116    ///
117    /// let distrib: Bernoulli<f64> = Bernoulli::new(0.2);
118    /// let mean: f64 = distrib.mean();
119    /// ```
120    fn mean(&self) -> T {
121        self.p
122    }
123
124    /// Variance
125    ///
126    /// # Example
127    ///
128    /// ```
129    /// use mathru::statistics::distrib::{Bernoulli, Discrete};
130    ///
131    /// let distrib: Bernoulli<f64> = Bernoulli::new(0.2);
132    /// let var: f64 = distrib.variance();
133    /// ```
134    fn variance(&self) -> T {
135        self.p * (T::one() - self.p)
136    }
137}
mathru/statistics/distrib/bernoulli.rs

mathru/statistics/distrib/
bernoulli.rs
