Struct statrs::distribution::Multinomial

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pub struct Multinomial { /* private fields */ }

Expand description

Implements the Multinomial distribution which is a generalization of the Binomial distribution

Examples

use statrs::distribution::Multinomial;
use statrs::statistics::MeanN;
use nalgebra::DVector;

let n = Multinomial::new(&[0.3, 0.7], 5).unwrap();
assert_eq!(n.mean().unwrap(), DVector::from_vec(vec![1.5, 3.5]));

Implementations

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impl Multinomial

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pub fn new(p: &[f64 ], n: u64) -> Result<Multinomial>

Constructs a new multinomial distribution with probabilities p and n number of trials.

Errors

Returns an error if p is empty, the sum of the elements in p is 0, or any element in p is less than 0 or is f64::NAN

Note

The elements in p do not need to be normalized

Examples

use statrs::distribution::Multinomial;

let mut result = Multinomial::new(&[0.0, 1.0, 2.0], 3);
assert!(result.is_ok());

result = Multinomial::new(&[0.0, -1.0, 2.0], 3);
assert!(result.is_err());

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pub fn p(&self) -> &[f64 ]

Returns the probabilities of the multinomial distribution as a slice

Examples

use statrs::distribution::Multinomial;

let n = Multinomial::new(&[0.0, 1.0, 2.0], 3).unwrap();
assert_eq!(n.p(), [0.0, 1.0, 2.0]);

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pub fn n(&self) -> u64

Returns the number of trials of the multinomial distribution

Examples

use statrs::distribution::Multinomial;

let n = Multinomial::new(&[0.0, 1.0, 2.0], 3).unwrap();
assert_eq!(n.n(), 3);

Trait Implementations

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impl Clone for Multinomial

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fn clone(&self) -> Multinomial

Returns a copy of the value. Read more

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

Performs copy-assignment from source. Read more

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impl Debug for Multinomial

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

Formats the value using the given formatter. Read more

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impl<'a> Discrete<&'a [u64 ], f64> for Multinomial

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fn pmf(&self, x: &[u64 ]) -> f64

Calculates the probability mass function for the multinomial distribution with the given x’s corresponding to the probabilities for this distribution

Panics

If the elements in x do not sum to n or if the length of x is not equivalent to the length of p

Formula

(n! / x_1!...x_k!) * p_i^x_i for i in 1...k

where n is the number of trials, p_i is the ith probability, x_i is the ith x value, and k is the total number of probabilities

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fn ln_pmf(&self, x: &[u64 ]) -> f64

Calculates the log probability mass function for the multinomial distribution with the given x’s corresponding to the probabilities for this distribution

Panics

If the elements in x do not sum to n or if the length of x is not equivalent to the length of p

Formula

ln((n! / x_1!...x_k!) * p_i^x_i) for i in 1...k

where n is the number of trials, p_i is the ith probability, x_i is the ith x value, and k is the total number of probabilities

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impl Distribution<Vec<f64, Global>> for Multinomial

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fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64>

Generate a random value of T, using rng as the source of randomness.

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fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
R: Rng,

Create an iterator that generates random values of T, using rng as the source of randomness. Read more

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fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S> where
F: Fn(T) -> S,

Create a distribution of values of ‘S’ by mapping the output of Self through the closure F Read more

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impl MeanN<Matrix<f64, Dynamic, Const<1_usize>, VecStorage<f64, Dynamic, Const<1_usize>>>> for Multinomial

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

Returns the mean of the multinomial distribution

Formula

n * p_i for i in 1...k

where n is the number of trials, p_i is the ith probability, and k is the total number of probabilities

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impl PartialEq<Multinomial> for Multinomial

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

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

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

This method tests for !=.

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impl VarianceN<Matrix<f64, Dynamic, Dynamic, VecStorage<f64, Dynamic, Dynamic>>> for Multinomial

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

Returns the variance of the multinomial distribution

Formula

n * p_i * (1 - p_i) for i in 1...k

where n is the number of trials, p_i is the ith probability, and k is the total number of probabilities

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impl StructuralPartialEq for Multinomial

Auto Trait Implementations

impl RefUnwindSafe for Multinomial

impl Send for Multinomial

impl Sync for Multinomial

impl Unpin for Multinomial

impl UnwindSafe for Multinomial

Blanket Implementations

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impl<T> Any for T where
T: 'static + ?Sized,

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pub fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more

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impl<T> Borrow<T> for T where
T: ?Sized,

const: unstable · source

pub fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more

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impl<T> BorrowMut<T> for T where
T: ?Sized,

const: unstable · source

pub fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more

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impl<T> From<T> for T

const: unstable · source

pub fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into for T where
U: From<T>,

const: unstable · source

pub fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T> Same<T> for T

type Output = T

Should always be Self

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impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,

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pub fn to_subset(&self) -> Option<SS>

The inverse inclusion map: attempts to construct self from the equivalent element of its superset. Read more

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pub fn is_in_subset(&self) -> bool

Checks if self is actually part of its subset T (and can be converted to it).

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pub fn to_subset_unchecked(&self) -> SS

Use with care! Same as self.to_subset but without any property checks. Always succeeds.

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pub fn from_subset(element: &SS) -> SP

The inclusion map: converts self to the equivalent element of its superset.

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impl<T> ToOwned for T where
T: Clone,

type Owned = T

The resulting type after obtaining ownership.

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pub fn to_owned(&self) -> T

Creates owned data from borrowed data, usually by cloning. Read more

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pub fn clone_into(&self, target: &mut T)

🔬 This is a nightly-only experimental API. (toowned_clone_into)

Uses borrowed data to replace owned data, usually by cloning. Read more

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impl<T, U> TryFrom for T where
U: Into<T>,

type Error = Infallible

The type returned in the event of a conversion error.

const: unstable · source

pub fn try_from(value: U) -> Result<T, <T as TryFrom>::Error>

Performs the conversion.

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impl<T, U> TryInto for T where
U: TryFrom<T>,

type Error = >::Error

The type returned in the event of a conversion error.

const: unstable · source

pub fn try_into(self) -> Result<U, >::Error>

Performs the conversion.

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impl<V, T> VZip<V> for T where
V: MultiLane<T>,

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Struct statrs::distribution::Multinomial

Implementations

impl Multinomial

pub fn new(p: &[f64], n: u64) -> Result<Multinomial>

pub fn p(&self) -> &[f64]

pub fn n(&self) -> u64

Trait Implementations

impl Clone for Multinomial

fn clone(&self) -> Multinomial

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

impl Debug for Multinomial

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

impl<'a> Discrete<&'a [u64], f64> for Multinomial

fn pmf(&self, x: &[u64]) -> f64

fn ln_pmf(&self, x: &[u64]) -> f64

impl Distribution<Vec<f64, Global>> for Multinomial

fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Vec<f64>

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where R: Rng,

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S> where F: Fn(T) -> S,

impl MeanN<Matrix<f64, Dynamic, Const<1_usize>, VecStorage<f64, Dynamic, Const<1_usize>>>> for Multinomial

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

impl PartialEq<Multinomial> for Multinomial

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

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

impl VarianceN<Matrix<f64, Dynamic, Dynamic, VecStorage<f64, Dynamic, Dynamic>>> for Multinomial

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

impl StructuralPartialEq for Multinomial

Auto Trait Implementations

impl RefUnwindSafe for Multinomial

impl Send for Multinomial

impl Sync for Multinomial

impl Unpin for Multinomial

impl UnwindSafe for Multinomial

Blanket Implementations

impl<T> Any for T where T: 'static + ?Sized,

pub fn type_id(&self) -> TypeId

impl<T> Borrow<T> for T where T: ?Sized,

pub fn borrow(&self) -> &T

impl<T> BorrowMut<T> for T where T: ?Sized,

pub fn borrow_mut(&mut self) -> &mut T

impl<T> From<T> for T

pub fn from(t: T) -> T

impl<T, U> Into<U> for T where U: From<T>,

pub fn into(self) -> U

impl<T> Same<T> for T

type Output = T

impl<SS, SP> SupersetOf<SS> for SP where SS: SubsetOf<SP>,

pub fn to_subset(&self) -> Option<SS>

pub fn is_in_subset(&self) -> bool

pub fn to_subset_unchecked(&self) -> SS

pub fn from_subset(element: &SS) -> SP

impl<T> ToOwned for T where T: Clone,

type Owned = T

pub fn to_owned(&self) -> T

pub fn clone_into(&self, target: &mut T)

impl<T, U> TryFrom<U> for T where U: Into<T>,

type Error = Infallible

pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

impl<T, U> TryInto<U> for T where U: TryFrom<T>,

type Error = <U as TryFrom<T>>::Error

pub fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

impl<V, T> VZip<V> for T where V: MultiLane<T>,

pub fn vzip(self) -> V

pub fn new(p: &[f64 ], n: u64) -> Result<Multinomial>

pub fn p(&self) -> &[f64 ]

impl<'a> Discrete<&'a [u64 ], f64> for Multinomial

fn pmf(&self, x: &[u64 ]) -> f64

fn ln_pmf(&self, x: &[u64 ]) -> f64

fn sample_iter<R>(self, rng: R) -> DistIter<Self, R, T> where
R: Rng,

fn map<F, S>(self, func: F) -> DistMap<Self, F, T, S> where
F: Fn(T) -> S,

impl<T> Any for T where
T: 'static + ?Sized,

impl<T> Borrow<T> for T where
T: ?Sized,

impl<T> BorrowMut<T> for T where
T: ?Sized,

impl<T, U> Into<U> for T where
U: From<T>,

impl<SS, SP> SupersetOf<SS> for SP where
SS: SubsetOf<SP>,

impl<T> ToOwned for T where
T: Clone,

impl<T, U> TryFrom<U> for T where
U: Into<T>,

impl<T, U> TryInto<U> for T where
U: TryFrom<T>,

impl<V, T> VZip<V> for T where
V: MultiLane<T>,