Struct Binomial 

pub struct Binomial { /* private fields */ }

Binomial claim counts: n independent risks, each claiming with probability p. Mean n p, variance n p (1 - p): under-dispersed.

use prospicio_prob::{Binomial, Counting};

let n = Binomial::new(10, 0.3).unwrap();
assert!((n.mean() - 3.0).abs() < 1e-15);
assert_eq!(n.pmf(11), 0.0);

Implementations

impl Binomial

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

Binomial with n trials and claim probability p in [0, 1). (p = 1 is a fixed count, outside the (a, b, 0) recursion.)

pub fn n(&self) -> u64

Number of trials.

pub fn p(&self) -> f64

Claim probability per trial.

Trait Implementations

impl Clone for Binomial

fn clone(&self) -> Binomial

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for Binomial

impl Counting for Binomial

fn pgf(&self, z: f64) -> f64

(1 + p (z - 1))^n.

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

P(N = k).

fn mean(&self) -> f64

E[N].

fn variance(&self) -> f64

Var[N].

fn panjer_ab(&self) -> (f64, f64)

(a, b) with p_k = (a + b / k) p_{k-1} for k ≥ 1.

fn pgf_complex(&self, (re, im): (f64, f64)) -> (f64, f64)

The pgf at a complex z = (re, im) with |z| ≤ 1, as (re, im). FFT aggregation applies it to the transform of the severity grid.

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

P(N ≤ k).

fn quantile(&self, p: f64) -> Result<u64>

Smallest k with P(N ≤ k) ≥ p. p = 1 gives u64::MAX.

fn sample(&self, rng: &mut StreamRng, n: usize) -> Vec<u64>

n counts from stream rng, by inverse transform.

impl Debug for Binomial

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

Formats the value using the given formatter.

impl PartialEq for Binomial

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

Equality operator ==.

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

Inequality operator !=.

impl StructuralPartialEq for Binomial