Struct rv::dist::Binomial

pub struct Binomial { /* fields omitted */ }

Binomial distribution with success probability p

Examples

use rv::prelude::*;

let binom = Binomial::new(4, 0.5).unwrap();
let cdf = binom.cdf(&2_u8);

assert_eq!(cdf, binom.pmf(&0_u8) + binom.pmf(&1_u8) + binom.pmf(&2_u8))

Values outside the support of [0, n] can cause panics in certain functions

let n = 4;
let binom = Binomial::new(n, 0.5).unwrap();
assert!(!binom.supports(&5_u8))

The maximum allowed value is 4, so the PMF of 5 cannot be computed

binom.pmf(&5_u8); // panics

Methods

impl Binomial

pub fn set_n(&mut self, val: u64) -> &mut Self

Total number of trials

pub fn set_p(&mut self, val: f64) -> &mut Self

Probability of a success

impl Binomial

pub fn new(n: u64, p: f64) -> Result<Self, BinomialError>

Create a new Binomial distribution

Arguments

• n: the total number of trials
• p: the pobability of success

pub fn new_unchecked(n: u64, p: f64) -> Self

Creates a new Binomial without checking whether the parameters are valid.

pub fn uniform(n: u64) -> Self

A Binomial distribution with a 50% chance of success

Example

let binom = Binomial::uniform(11);
assert_eq!(binom.p(), 0.5);

pub fn n(&self) -> u64

Get the number of trials

Example

let binom = Binomial::uniform(11);
assert_eq!(binom, Binomial::new(11, 0.5).unwrap());

pub fn p(&self) -> f64

Get the probability of success

Example

let binom = Binomial::new(10, 0.2).unwrap();
assert_eq!(binom.p(), 0.2);

pub fn q(&self) -> f64

The complement of p, i.e. (1 - p).

Example

let binom = Binomial::new(10, 0.2).unwrap();
assert_eq!(binom.q(), 0.8);

Trait Implementations

impl Cdf<i16> for Binomial

fn cdf(&self, k: &i16) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<i32> for Binomial

fn cdf(&self, k: &i32) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<i64> for Binomial

fn cdf(&self, k: &i64) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<i8> for Binomial

fn cdf(&self, k: &i8) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<u16> for Binomial

fn cdf(&self, k: &u16) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<u32> for Binomial

fn cdf(&self, k: &u32) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<u64> for Binomial

fn cdf(&self, k: &u64) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<u8> for Binomial

fn cdf(&self, k: &u8) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Cdf<usize> for Binomial

fn cdf(&self, k: &usize) -> f64

The value of the Cumulative Density Function at x

fn sf(&self, x: &X) -> f64

Survival function, 1 - CDF(x)

impl Clone for Binomial

fn clone(&self) -> Binomial

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Binomial

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl DiscreteDistr<i16> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<i32> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<i64> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<i8> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<u16> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<u32> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<u64> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<u8> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl DiscreteDistr<usize> for Binomial

fn pmf(&self, x: &X) -> f64

Probability mass function (PMF) at x

fn ln_pmf(&self, x: &X) -> f64

Natural logarithm of the probability mass function (PMF)

impl Display for Binomial

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl<'_> From<&'_ Binomial> for String

fn from(b: &Binomial) -> String

Performs the conversion.

impl Kurtosis for Binomial

fn kurtosis(&self) -> Option<f64>

impl Mean<f64> for Binomial

fn mean(&self) -> Option<f64>

Returns None if the mean is undefined

impl PartialEq<Binomial> for Binomial

fn eq(&self, other: &Binomial) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Binomial) -> bool

This method tests for !=.

impl PartialOrd<Binomial> for Binomial

fn partial_cmp(&self, other: &Binomial) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

fn lt(&self, other: &Binomial) -> bool

This method tests less than (for self and other) and is used by the < operator.

fn le(&self, other: &Binomial) -> bool

This method tests less than or equal to (for self and other) and is used by the <= operator.

fn gt(&self, other: &Binomial) -> bool

This method tests greater than (for self and other) and is used by the > operator.

fn ge(&self, other: &Binomial) -> bool

This method tests greater than or equal to (for self and other) and is used by the >= operator.

impl Rv<i16> for Binomial

fn ln_f(&self, k: &i16) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> i16

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<i32> for Binomial

fn ln_f(&self, k: &i32) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> i32

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<i64> for Binomial

fn ln_f(&self, k: &i64) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> i64

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<i8> for Binomial

fn ln_f(&self, k: &i8) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> i8

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<u16> for Binomial

fn ln_f(&self, k: &u16) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> u16

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<u32> for Binomial

fn ln_f(&self, k: &u32) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> u32

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<u64> for Binomial

fn ln_f(&self, k: &u64) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> u64

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<u8> for Binomial

fn ln_f(&self, k: &u8) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> u8

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Rv<usize> for Binomial

fn ln_f(&self, k: &usize) -> f64

Probability function

fn draw<R: Rng>(&self, rng: &mut R) -> usize

Single draw from the Rv

fn f(&self, x: &X) -> f64

Probability function

fn sample<R: Rng>(&self, n: usize, rng: &mut R) -> Vec<X>

Multiple draws of the Rv

impl Skewness for Binomial

fn skewness(&self) -> Option<f64>

impl StructuralPartialEq for Binomial

impl Support<i16> for Binomial

fn supports(&self, k: &i16) -> bool

Returns true if x is in the support of the Rv

impl Support<i32> for Binomial

fn supports(&self, k: &i32) -> bool

Returns true if x is in the support of the Rv

impl Support<i64> for Binomial

fn supports(&self, k: &i64) -> bool

Returns true if x is in the support of the Rv

impl Support<i8> for Binomial

fn supports(&self, k: &i8) -> bool

Returns true if x is in the support of the Rv

impl Support<u16> for Binomial

fn supports(&self, k: &u16) -> bool

Returns true if x is in the support of the Rv

impl Support<u32> for Binomial

fn supports(&self, k: &u32) -> bool

Returns true if x is in the support of the Rv

impl Support<u64> for Binomial

fn supports(&self, k: &u64) -> bool

Returns true if x is in the support of the Rv

impl Support<u8> for Binomial

fn supports(&self, k: &u8) -> bool

Returns true if x is in the support of the Rv

impl Support<usize> for Binomial

fn supports(&self, k: &usize) -> bool

Returns true if x is in the support of the Rv

impl Variance<f64> for Binomial

fn variance(&self) -> Option<f64>

Returns None if the variance is undefined