Struct Poisson 

pub struct Poisson { /* private fields */ }

Poisson claim counts with mean lambda.

use prospicio_prob::{Counting, Poisson};

let n = Poisson::new(3.0).unwrap();
assert!((n.pmf(0) - (-3f64).exp()).abs() < 1e-15);
assert_eq!(n.panjer_ab(), (0.0, 3.0));

Implementations

impl Poisson

pub fn new(lambda: f64) -> Result<Self>

Poisson with mean lambda; fails unless lambda is finite and non-negative.

pub fn lambda(&self) -> f64

The mean.

Trait Implementations

impl Clone for Poisson

fn clone(&self) -> Poisson

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for Poisson

impl Counting for Poisson

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

exp(lambda (z - 1)).

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 Poisson

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

Formats the value using the given formatter.

impl PartialEq for Poisson

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

Equality operator ==.

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

Inequality operator !=.

impl StructuralPartialEq for Poisson